Business
Organizational Management & Leadership ISBN 13:978-1-934748-11-4
Chapter 5-6
Term – Social Networking Sites
1. After reading the articles, select the 1 article that you wish to discuss. Your thread must include the information listed below in the following format and be posted directly in the discussion board:
· Definition: a brief definition of the key term followed by the APA reference for the term; this does not count in the word requirement;
· Summary: Choose 1 of the articles and summarize it in your own words. This must be about 125 word minimum. Be sure to note the article’s author as well as his/her credentials and the reason his/her opinions, research, or findings should be respected regarding the key term.
· Discussion: Using a minimum of 400 words, write a brief discussion in your own words of how the article relates to the selected key term. A discussion is not rehashing what was already stated in the article, but rather the opportunity for you to add value to the discussion by integrating the other research performed. This is the most important part of the thread.
· Biblical Integration: You must integrate your key term with a biblical truth. To do so, you may choose to answer a question provided at the end of each chapter or utilize another Bible verse. Integration of biblical truth is not simply listing a Bible verse but connecting the Scripture to the concept being covered. This section must be a minimum of 100 words.
· References: All references must be listed at the bottom of the thread in current APA format.
Be sure to use the headers (Definition, Summary, Discussion) in your thread to ensure that all aspects of the assignment are completed as required.
Social Network Sites: Definition, History,
and Scholarship
danah m. boyd
School of Information
University of California-Berkeley
Nicole B. Ellison
Department of Telecommunication, Information Studies, and Media
Michigan State University
Social network sites (SNSs) are increasingly attracting the attention of academic and
industry researchers intrigued by their affordances and reach. This special theme section
of the Journal of Computer-Mediated Communication brings together scholarship on
these emergent phenomena. In this introductory article, we describe features of SNSs
and propose a comprehensive definition. We then present one perspective on the history
of such sites, discussing key changes and developments. After briefly summarizing exist-
ing scholarship concerning SNSs, we discuss the articles in this special section and con-
clude with considerations for future research.
doi:10.1111/j.1083-6101.2007.00393.x
Introduction
Since their introduction, social network sites (SNSs) such as MySpace, Facebook,
Cyworld, and Bebo have attracted millions of users, many of whom have integrated
these sites into their daily practices. As of this writing, there are hundreds of SNSs,
with various technological affordances, supporting a wide range of interests and
practices. While their key technological features are fairly consistent, the cultures
that emerge around SNSs are varied. Most sites support the maintenance of pre-
existing social networks, but others help strangers connect based on shared interests,
political views, or activities. Some sites cater to diverse audiences, while others attract
people based on common language or shared racial, sexual, religious, or nationality-
based identities. Sites also vary in the extent to which they incorporate new infor-
mation and communication tools, such as mobile connectivity, blogging, and photo/
video-sharing.
Journal of Computer-Mediated Communication
210 Journal of Computer-Mediated Communication 13 (2008) 210–230 ª 2008 International Communication Association
Scholars from disparate fields have examined SNSs in order to understand the
practices, implications, culture, and meaning of the sites, as well as users’ engage-
ment with them. This special theme section of the Journal of Computer-Mediated
Communication brings together a unique collection of articles that analyze a wide
spectrum of social network sites using various methodological techniques, theoret-
ical traditions, and analytic approaches. By collecting these articles in this issue, our
goal is to showcase some of the interdisciplinary scholarship around these sites.
The purpose of this introduction is to provide a conceptual, historical, and
scholarly context for the articles in this collection. We begin by defining what con-
stitutes a social network site and then present one perspective on the historical
development of SNSs, drawing from personal interviews and public accounts of sites
and their changes over time. Following this, we review recent scholarship on SNSs
and attempt to contextualize and highlight key works. We conclude with a descrip-
tion of the articles included in this special section and suggestions for future research.
Social Network Sites: A Definition
We define social network sites as web-based services that allow individuals to (1)
construct a public or semi-public profile within a bounded system, (2) articulate
a list of other users with whom they share a connection, and (3) view and traverse
their list of connections and those made by others within the system. The nature and
nomenclature of these connections may vary from site to site.
While we use the term ‘‘social network site’’ to describe this phenomenon, the
term ‘‘social networking sites’’ also appears in public discourse, and the two terms are
often used interchangeably. We chose not to employ the term ‘‘networking’’ for two
reasons: emphasis and scope. ‘‘Networking’’ emphasizes relationship initiation, often
between strangers. While networking is possible on these sites, it is not the primary
practice on many of them, nor is it what differentiates them from other forms of
computer-mediated communication (CMC).
What makes social network sites unique is not that they allow individuals to meet
strangers, but rather that they enable users to articulate and make visible their social
networks. This can result in connections between individuals that would not other-
wise be made, but that is often not the goal, and these meetings are frequently
between ‘‘latent ties’’ (Haythornthwaite, 2005) who share some offline connection.
On many of the large SNSs, participants are not necessarily ‘‘networking’’ or looking
to meet new people; instead, they are primarily communicating with people who are
already a part of their extended social network. To emphasize this articulated social
network as a critical organizing feature of these sites, we label them ‘‘social network
sites.’’
While SNSs have implemented a wide variety of technical features, their back-
bone consists of visible profiles that display an articulated list of Friends1 who are
also users of the system. Profiles are unique pages where one can ‘‘type oneself into
being’’ (Sundén, 2003, p. 3). After joining an SNS, an individual is asked to fill out
Journal of Computer-Mediated Communication 13 (2008) 210–230 ª 2008 International Communication Association 211
Figure 1 Timeline of the launch dates of many major SNSs and dates when community sites
re-launched with SNS features
212 Journal of Computer-Mediated Communication 13 (2008) 210–230 ª 2008 International Communication Association
forms containing a series of questions. The profile is generated using the answers to
these questions, which typically include descriptors such as age, location, interests,
and an ‘‘about me’’ section. Most sites also encourage users to upload a profile photo.
Some sites allow users to enhance their profiles by adding multimedia content or
modifying their profile’s look and feel. Others, such as Facebook, allow users to add
modules (‘‘Applications’’) that enhance their profile.
The visibility of a profile varies by site and according to user discretion. By
default, profiles on Friendster and Tribe.net are crawled by search engines, making
them visible to anyone, regardless of whether or not the viewer has an account.
Alternatively, LinkedIn controls what a viewer may see based on whether she or
he has a paid account. Sites like MySpace allow users to choose whether they want
their profile to be public or ‘‘Friends only.’’ Facebook takes a different approach—by
default, users who are part of the same ‘‘network’’ can view each other’s profiles,
unless a profile owner has decided to deny permission to those in their network.
Structural variations around visibility and access are one of the primary ways that
SNSs differentiate themselves from each other.
After joining a social network site, users are prompted to identify others in the
system with whom they have a relationship. The label for these relationships differs
depending on the site—popular terms include ‘‘Friends,’’ ‘‘Contacts,’’ and ‘‘Fans.’’
Most SNSs require bi-directional confirmation for Friendship, but some do not.
These one-directional ties are sometimes labeled as ‘‘Fans’’ or ‘‘Followers,’’ but many
sites call these Friends as well. The term ‘‘Friends’’ can be misleading, because the
connection does not necessarily mean friendship in the everyday vernacular sense,
and the reasons people connect are varied (boyd, 2006a).
The public display of connections is a crucial component of SNSs. The Friends
list contains links to each Friend’s profile, enabling viewers to traverse the network
graph by clicking through the Friends lists. On most sites, the list of Friends is visible
to anyone who is permitted to view the profile, although there are exceptions. For
instance, some MySpace users have hacked their profiles to hide the Friends display,
and LinkedIn allows users to opt out of displaying their network.
Most SNSs also provide a mechanism for users to leave messages on their
Friends’ profiles. This feature typically involves leaving ‘‘comments,’’ although sites
employ various labels for this feature. In addition, SNSs often have a private mes-
saging feature similar to webmail. While both private messages and comments are
popular on most of the major SNSs, they are not universally available.
Not all social network sites began as such. QQ started as a Chinese instant
messaging service, LunarStorm as a community site, Cyworld as a Korean discussion
forum tool, and Skyrock (formerly Skyblog) was a French blogging service before
adding SNS features. Classmates.com, a directory of school affiliates launched in
1995, began supporting articulated lists of Friends after SNSs became popular.
AsianAvenue, MiGente, and BlackPlanet were early popular ethnic community sites
with limited Friends functionality before re-launching in 2005–2006 with SNS
features and structure.
Journal of Computer-Mediated Communication 13 (2008) 210–230 ª 2008 International Communication Association 213
Beyond profiles, Friends, comments, and private messaging, SNSs vary greatly in
their features and user base. Some have photo-sharing or video-sharing capabilities;
others have built-in blogging and instant messaging technology. There are mobile-
specific SNSs (e.g., Dodgeball), but some web-based SNSs also support limited
mobile interactions (e.g., Facebook, MySpace, and Cyworld). Many SNSs target
people from specific geographical regions or linguistic groups, although this does
not always determine the site’s constituency. Orkut, for example, was launched in the
United States with an English-only interface, but Portuguese-speaking Brazilians
quickly became the dominant user group (Kopytoff, 2004). Some sites are designed
with specific ethnic, religious, sexual orientation, political, or other identity-driven
categories in mind. There are even SNSs for dogs (Dogster) and cats (Catster),
although their owners must manage their profiles.
While SNSs are often designed to be widely accessible, many attract homoge-
neous populations initially, so it is not uncommon to find groups using sites to
segregate themselves by nationality, age, educational level, or other factors that
typically segment society (Hargittai, this issue), even if that was not the intention
of the designers.
A History of Social Network Sites
The Early Years
According to the definition above, the first recognizable social network site launched
in 1997. SixDegrees.com allowed users to create profiles, list their Friends and,
beginning in 1998, surf the Friends lists. Each of these features existed in some form
before SixDegrees, of course. Profiles existed on most major dating sites and many
community sites. AIM and ICQ buddy lists supported lists of Friends, although those
Friends were not visible to others. Classmates.com allowed people to affiliate with
their high school or college and surf the network for others who were also affiliated,
but users could not create profiles or list Friends until years later. SixDegrees was the
first to combine these features.
SixDegrees promoted itself as a tool to help people connect with and send
messages to others. While SixDegrees attracted millions of users, it failed to become
a sustainable business and, in 2000, the service closed. Looking back, its founder
believes that SixDegrees was simply ahead of its time (A. Weinreich, personal com-
munication, July 11, 2007). While people were already flocking to the Internet, most
did not have extended networks of friends who were online. Early adopters com-
plained that there was little to do after accepting Friend requests, and most users
were not interested in meeting strangers.
From 1997 to 2001, a number of community tools began supporting various
combinations of profiles and publicly articulated Friends. AsianAvenue, BlackPlanet,
and MiGente allowed users to create personal, professional, and dating profiles—
users could identify Friends on their personal profiles without seeking approval for
those connections (O. Wasow, personal communication, August 16, 2007). Likewise,
214 Journal of Computer-Mediated Communication 13 (2008) 210–230 ª 2008 International Communication Association
shortly after its launch in 1999, LiveJournal listed one-directional connections on
user pages. LiveJournal’s creator suspects that he fashioned these Friends after
instant messaging buddy lists (B. Fitzpatrick, personal communication, June 15,
2007)—on LiveJournal, people mark others as Friends to follow their journals and
manage privacy settings. The Korean virtual worlds site Cyworld was started in 1999
and added SNS features in 2001, independent of these other sites (see Kim & Yun,
this issue). Likewise, when the Swedish web community LunarStorm refashioned
itself as an SNS in 2000, it contained Friends lists, guestbooks, and diary pages
(D. Skog, personal communication, September 24, 2007).
The next wave of SNSs began when Ryze.com was launched in 2001 to help
people leverage their business networks. Ryze’s founder reports that he first intro-
duced the site to his friends—primarily members of the San Francisco business and
technology community, including the entrepreneurs and investors behind many
future SNSs (A. Scott, personal communication, June 14, 2007). In particular, the
people behind Ryze, Tribe.net, LinkedIn, and Friendster were tightly entwined per-
sonally and professionally. They believed that they could support each other without
competing (Festa, 2003). In the end, Ryze never acquired mass popularity, Tribe.net
grew to attract a passionate niche user base, LinkedIn became a powerful business
service, and Friendster became the most significant, if only as ‘‘one of the biggest
disappointments in Internet history’’ (Chafkin, 2007, p. 1).
Like any brief history of a major phenomenon, ours is necessarily incomplete. In
the following section we discuss Friendster, MySpace, and Facebook, three key SNSs
that shaped the business, cultural, and research landscape.
The Rise (and Fall) of Friendster
Friendster launched in 2002 as a social complement to Ryze. It was designed to
compete with Match.com, a profitable online dating site (Cohen, 2003). While most
dating sites focused on introducing people to strangers with similar interests, Friend-
ster was designed to help friends-of-friends meet, based on the assumption that
friends-of-friends would make better romantic partners than would strangers (J.
Abrams, personal communication, March 27, 2003). Friendster gained traction among
three groups of early adopters who shaped the site—bloggers, attendees of the Burning
Man arts festival, and gay men (boyd, 2004)—and grew to 300,000 users through word
of mouth before traditional press coverage began in May 2003 (O’Shea, 2003).
As Friendster’s popularity surged, the site encountered technical and social dif-
ficulties (boyd, 2006b). Friendster’s servers and databases were ill-equipped to han-
dle its rapid growth, and the site faltered regularly, frustrating users who replaced
email with Friendster. Because organic growth had been critical to creating a coherent
community, the onslaught of new users who learned about the site from media
coverage upset the cultural balance. Furthermore, exponential growth meant a col-
lapse in social contexts: Users had to face their bosses and former classmates along-
side their close friends. To complicate matters, Friendster began restricting the
activities of its most passionate users.
Journal of Computer-Mediated Communication 13 (2008) 210–230 ª 2008 International Communication Association 215
The initial design of Friendster restricted users from viewing profiles of people
who were more than four degrees away (friends-of-friends-of-friends-of-friends). In
order to view additional profiles, users began adding acquaintances and interesting-
looking strangers to expand their reach. Some began massively collecting Friends, an
activity that was implicitly encouraged through a ‘‘most popular’’ feature. The ulti-
mate collectors were fake profiles representing iconic fictional characters: celebrities,
concepts, and other such entities. These ‘‘Fakesters’’ outraged the company, who
banished fake profiles and eliminated the ‘‘most popular’’ feature (boyd, in press-b).
While few people actually created Fakesters, many more enjoyed surfing Fakesters for
entertainment or using functional Fakesters (e.g., ‘‘Brown University’’) to find peo-
ple they knew.
The active deletion of Fakesters (and genuine users who chose non-realistic
photos) signaled to some that the company did not share users’ interests. Many
early adopters left because of the combination of technical difficulties, social colli-
sions, and a rupture of trust between users and the site (boyd, 2006b). However, at
the same time that it was fading in the U.S., its popularity skyrocketed in the
Philippines, Singapore, Malaysia, and Indonesia (Goldberg, 2007).
SNSs Hit the Mainstream
From 2003 onward, many new SNSs were launched, prompting social software
analyst Clay Shirky (2003) to coin the term YASNS: ‘‘Yet Another Social Networking
Service.’’ Most took the form of profile-centric sites, trying to replicate the early
success of Friendster or target specific demographics. While socially-organized SNSs
solicit broad audiences, professional sites such as LinkedIn, Visible Path, and Xing
(formerly openBC) focus on business people. ‘‘Passion-centric’’ SNSs like Dogster
(T. Rheingold, personal communication, August 2, 2007) help strangers connect
based on shared interests. Care2 helps activists meet, Couchsurfing connects travelers
to people with couches, and MyChurch joins Christian churches and their members.
Furthermore, as the social media and user-generated content phenomena grew,
websites focused on media sharing began implementing SNS features and becoming
SNSs themselves. Examples include Flickr (photo sharing), Last.FM (music listening
habits), and YouTube (video sharing).
With the plethora of venture-backed startups launching in Silicon Valley, few
people paid attention to SNSs that gained popularity elsewhere, even those built by
major corporations. For example, Google’s Orkut failed to build a sustainable U.S.
user base, but a ‘‘Brazilian invasion’’ (Fragoso, 2006) made Orkut the national SNS of
Brazil. Microsoft’s Windows Live Spaces (a.k.a. MSN Spaces) also launched to luke-
warm U.S. reception but became extremely popular elsewhere.
Few analysts or journalists noticed when MySpace launched in Santa Monica,
California, hundreds of miles from Silicon Valley. MySpace was begun in 2003 to
compete with sites like Friendster, Xanga, and AsianAvenue, according to co-
founder Tom Anderson (personal communication, August 2, 2007); the founders
wanted to attract estranged Friendster users (T. Anderson, personal communication,
216 Journal of Computer-Mediated Communication 13 (2008) 210–230 ª 2008 International Communication Association
February 2, 2006). After rumors emerged that Friendster would adopt a fee-based
system, users posted Friendster messages encouraging people to join alternate SNSs,
including Tribe.net and MySpace (T. Anderson, personal communication, August 2,
2007). Because of this, MySpace was able to grow rapidly by capitalizing on Friend-
ster’s alienation of its early adopters. One particularly notable group that encouraged
others to switch were indie-rock bands who were expelled from Friendster for failing
to comply with profile regulations.
While MySpace was not launched with bands in mind, they were welcomed.
Indie-rock bands from the Los Angeles region began creating profiles, and local
promoters used MySpace to advertise VIP passes for popular clubs. Intrigued,
MySpace contacted local musicians to see how they could support them (T. Anderson,
personal communication, September 28, 2006). Bands were not the sole source of
MySpace growth, but the symbiotic relationship between bands and fans helped
MySpace expand beyond former Friendster users. The bands-and-fans dynamic
was mutually beneficial: Bands wanted to be able to contact fans, while fans desired
attention from their favorite bands and used Friend connections to signal identity
and affiliation.
Futhermore, MySpace differentiated itself by regularly adding features based on
user demand (boyd, 2006b) and by allowing users to personalize their pages. This
‘‘feature’’ emerged because MySpace did not restrict users from adding HTML into
the forms that framed their profiles; a copy/paste code culture emerged on the web to
support users in generating unique MySpace backgrounds and layouts (Perkel, in
press).
Teenagers began joining MySpace en masse in 2004. Unlike older users, most
teens were never on Friendster—some joined because they wanted to connect with
their favorite bands; others were introduced to the site through older family mem-
bers. As teens began signing up, they encouraged their friends to join. Rather than
rejecting underage users, MySpace changed its user policy to allow minors. As the site
grew, three distinct populations began to form: musicians/artists, teenagers, and the
post-college urban social crowd. By and large, the latter two groups did not interact
with one another except through bands. Because of the lack of mainstream press
coverage during 2004, few others noticed the site’s growing popularity.
Then, in July 2005, News Corporation purchased MySpace for $580 million
(BBC, 2005), attracting massive media attention. Afterwards, safety issues plagued
MySpace. The site was implicated in a series of sexual interactions between adults
and minors, prompting legal action (Consumer Affairs, 2006). A moral panic con-
cerning sexual predators quickly spread (Bahney, 2006), although research suggests
that the concerns were exaggerated.
2
A Global Phenomenon
While MySpace attracted the majority of media attention in the U.S. and abroad,
SNSs were proliferating and growing in popularity worldwide. Friendster gained
traction in the Pacific Islands, Orkut became the premier SNS in Brazil before
Journal of Computer-Mediated Communication 13 (2008) 210–230 ª 2008 International Communication Association 217
growing rapidly in India (Madhavan, 2007), Mixi attained widespread adoption in
Japan, LunarStorm took off in Sweden, Dutch users embraced Hyves, Grono cap-
tured Poland, Hi5 was adopted in smaller countries in Latin America, South Amer-
ica, and Europe, and Bebo became very popular in the United Kingdom, New
Zealand, and Australia. Additionally, previously popular communication and com-
munity services began implementing SNS features. The Chinese QQ instant messag-
ing service instantly became the largest SNS worldwide when it added profiles and
made friends visible (McLeod, 2006), while the forum tool Cyworld cornered the
Korean market by introducing homepages and buddies (Ewers, 2006).
Blogging services with complete SNS features also became popular. In the U.S.,
blogging tools with SNS features, such as Xanga, LiveJournal, and Vox, attracted
broad audiences. Skyrock reigns in France, and Windows Live Spaces dominates
numerous markets worldwide, including in Mexico, Italy, and Spain. Although SNSs
like QQ, Orkut, and Live Spaces are just as large as, if not larger than, MySpace, they
receive little coverage in U.S. and English-speaking media, making it difficult to track
their trajectories.
Expanding Niche Communities
Alongside these open services, other SNSs launched to support niche demographics
before expanding to a broader audience. Unlike previous SNSs, Facebook was
designed to support distinct college networks only. Facebook began in early 2004
as a Harvard-only SNS (Cassidy, 2006). To join, a user had to have a harvard.edu
email address. As Facebook began supporting other schools, those users were also
required to have university email addresses associated with those institutions,
a requirement that kept the site relatively closed and contributed to users’ percep-
tions of the site as an intimate, private community.
Beginning in September 2005, Facebook expanded to include high school students,
professionals inside corporate networks, and, eventually, everyone. The change to open
signup did not mean that new users could easily access users in closed networks—
gaining access to corporate networks still required the appropriate .com address, while
gaining access to high school networks required administrator approval. (As of this
writing, only membership in regional networks requires no permission.) Unlike other
SNSs, Facebook users are unable to make their full profiles public to all users. Another
feature that differentiates Facebook is the ability for outside developers to build
‘‘Applications’’ which allow users to personalize their profiles and perform other tasks,
such as compare movie preferences and chart travel histories.
While most SNSs focus on growing broadly and exponentially, others explicitly
seek narrower audiences. Some, like aSmallWorld and BeautifulPeople, intentionally
restrict access to appear selective and elite. Others—activity-centered sites like
Couchsurfing, identity-driven sites like BlackPlanet, and affiliation-focused sites like
MyChurch—are limited by their target demographic and thus tend to be smaller.
Finally, anyone who wishes to create a niche social network site can do so on Ning,
a platform and hosting service that encourages users to create their own SNSs.
218 Journal of Computer-Mediated Communication 13 (2008) 210–230 ª 2008 International Communication Association
Currently, there are no reliable data regarding how many people use SNSs,
although marketing research indicates that SNSs are growing in popularity world-
wide (comScore, 2007). This growth has prompted many corporations to invest time
and money in creating, purchasing, promoting, and advertising SNSs. At the same
time, other companies are blocking their employees from accessing the sites. Addi-
tionally, the U.S. military banned soldiers from accessing MySpace (Frosch, 2007)
and the Canadian government prohibited employees from Facebook (Benzie, 2007),
while the U.S. Congress has proposed legislation to ban youth from accessing SNSs in
schools and libraries (H.R. 5319, 2006; S. 49, 2007).
The rise of SNSs indicates a shift in the organization of online communities.
While websites dedicated to communities of interest still exist and prosper, SNSs are
primarily organized around people, not interests. Early public online communities
such as Usenet and public discussion forums were structured by topics or according to
topical hierarchies, but social network sites are structured as personal (or ‘‘egocentric’’)
networks, with the individual at the center of their own community. This more
accurately mirrors unmediated social structures, where ‘‘the world is composed of
networks, not groups’’ (Wellman, 1988, p. 37). The introduction of SNS features has
introduced a new organizational framework for online communities, and with it,
a vibrant new research context.
Previous Scholarship
Scholarship concerning SNSs is emerging from diverse disciplinary and methodo-
logical traditions, addresses a range of topics, and builds on a large body of CMC
research. The goal of this section is to survey research that is directly concerned with
social network sites, and in so doing, to set the stage for the articles in this special
issue. To date, the bulk of SNS research has focused on impression management and
friendship performance, networks and network structure, online/offline connec-
tions, and privacy issues.
Impression Management and Friendship Performance
Like other online contexts in which individuals are consciously able to construct an
online representation of self—such as online dating profiles and MUDS—SNSs
constitute an important research context for scholars investigating processes of impres-
sion management, self-presentation, and friendship performance. In one of the earliest
academic articles on SNSs, boyd (2004) examined Friendster as a locus of publicly
articulated social networks that allowed users to negotiate presentations of self and
connect with others. Donath and boyd (2004) extended this to suggest that ‘‘public
displays of connection’’ serve as important identity signals that help people navigate
the networked social world, in that an extended network may serve to validate identity
information presented in profiles.
While most sites encourage users to construct accurate representations of them-
selves, participants do this to varying degrees. Marwick (2005) found that users on
Journal of Computer-Mediated Communication 13 (2008) 210–230 ª 2008 International Communication Association 219
three different SNSs had complex strategies for negotiating the rigidity of a prescribed
‘‘authentic’’ profile, while boyd (in press-b) examined the phenomenon of ‘‘Fakest-
ers’’ and argued that profiles could never be ‘‘real.’’ The extent to which portraits are
authentic or playful varies across sites; both social and technological forces shape
user practices. Skog (2005) found that the status feature on LunarStorm strongly
influenced how people behaved and what they choose to reveal—profiles there
indicate one’s status as measured by activity (e.g., sending messages) and indicators
of authenticity (e.g., using a ‘‘real’’ photo instead of a drawing).
Another aspect of self-presentation is the articulation of friendship links, which
serve as identity markers for the profile owner. Impression management is one of the
reasons given by Friendster users for choosing particular friends (Donath & boyd,
2004). Recognizing this, Zinman and Donath (2007) noted that MySpace spammers
leverage people’s willingness to connect to interesting people to find targets for their
spam.
In their examination of LiveJournal ‘‘friendship,’’ Fono and Raynes-Goldie
(2006) described users’ understandings regarding public displays of connections
and how the Friending function can operate as a catalyst for social drama. In listing
user motivations for Friending, boyd (2006a) points out that ‘‘Friends’’ on SNSs are
not the same as ‘‘friends’’ in the everyday sense; instead, Friends provide context by
offering users an imagined audience to guide behavioral norms. Other work in this
area has examined the use of Friendster Testimonials as self-presentational devices
(boyd & Heer, 2006) and the extent to which the attractiveness of one’s Friends (as
indicated by Facebook’s ‘‘Wall’’ feature) impacts impression formation (Walther,
Van Der Heide, Kim, & Westerman, in press).
Networks and Network Structure
Social network sites also provide rich sources of naturalistic behavioral data. Profile
and linkage data from SNSs can be gathered either through the use of automated
collection techniques or through datasets provided directly from the company,
enabling network analysis researchers to explore large-scale patterns of friending,
usage, and other visible indicators (Hogan, in press), and continuing an analysis
trend that started with examinations of blogs and other websites. For instance,
Golder, Wilkinson, and Huberman (2007) examined an anonymized dataset con-
sisting of 362 million messages exchanged by over four million Facebook users for
insight into Friending and messaging activities. Lampe, Ellison, and Steinfield (2007)
explored the relationship between profile elements and number of Facebook friends,
finding that profile fields that reduce transaction costs and are harder to falsify are
most likely to be associated with larger number of friendship links. These kinds of
data also lend themselves well to analysis through network visualization (Adamic,
Buyukkokten, & Adar, 2003; Heer & boyd, 2005; Paolillo & Wright, 2005).
SNS researchers have also studied the network structure of Friendship. Analyzing
the roles people played in the growth of Flickr and Yahoo! 360’s networks, Kumar,
Novak, and Tomkins (2006) argued that there are passive members, inviters, and
220 Journal of Computer-Mediated Communication 13 (2008) 210–230 ª 2008 International Communication Association
linkers ‘‘who fully participate in the social evolution of the network’’ (p. 1). Scholar-
ship concerning LiveJournal’s network has included a Friendship classification
scheme (Hsu, Lancaster, Paradesi, & Weniger, 2007), an analysis of the role of
language in the topology of Friendship (Herring et al., 2007), research into the
importance of geography in Friending (Liben-Nowell, Novak, Kumar, Raghavan,
and Tomkins, 2005), and studies on what motivates people to join particular com-
munities (Backstrom, Huttenlocher, Kleinberg, & Lan, 2006). Based on Orkut data,
Spertus, Sahami, and Buyukkokten (2005) identified a topology of users through
their membership in certain communities; they suggest that sites can use this to
recommend additional communities of interest to users. Finally, Liu, Maes, and
Davenport (2006) argued that Friend connections are not the only network structure
worth investigating. They examined the ways in which the performance of tastes
(favorite music, books, film, etc.) constitutes an alternate network structure, which
they call a ‘‘taste fabric.’’
Bridging Online and Offline Social Networks
Although exceptions exist, the available research suggests that most SNSs primarily
support pre-existing social relations. Ellison, Steinfield, and Lampe (2007) suggest
that Facebook is used to maintain existing offline relationships or solidify offline
connections, as opposed to meeting new people. These relationships may be weak
ties, but typically there is some common offline element among individuals who
friend one another, such as a shared class at school. This is one of the chief dimen-
sions that differentiate SNSs from earlier forms of public CMC such as newsgroups
(Ellison et al., 2007). Research in this vein has investigated how online interactions
interface with offline ones. For instance, Lampe, Ellison, and Steinfield (2006) found
that Facebook users engage in ‘‘searching’’ for people with whom they have an offline
connection more than they ‘‘browse’’ for complete strangers to meet. Likewise, Pew
research found that 91% of U.S. teens who use SNSs do so to connect with friends
(Lenhart & Madden, 2007).
Given that SNSs enable individuals to connect with one another, it is not sur-
prising that they have become deeply embedded in user’s lives. In Korea, Cyworld
has become an integral part of everyday life—Choi (2006) found that 85% of that
study’s respondents ‘‘listed the maintenance and reinforcement of pre-existing social
networks as their main motive for Cyworld use’’ (p. 181). Likewise, boyd (2008)
argues that MySpace and Facebook enable U.S. youth to socialize with their friends
even when they are unable to gather in unmediated situations; she argues that
SNSs are ‘‘networked publics’’ that support sociability, just as unmediated public
spaces do.
Privacy
Popular press coverage of SNSs has emphasized potential privacy concerns, primarily
concerning the safety of younger users (George, 2006; Kornblum & Marklein, 2006).
Researchers have investigated the potential threats to privacy associated with SNSs.
Journal of Computer-Mediated Communication 13 (2008) 210–230 ª 2008 International Communication Association 221
In one of the first academic studies of privacy and SNSs, Gross and Acquisti (2005)
analyzed 4,000 Carnegie Mellon University Facebook profiles and outlined the
potential threats to privacy contained in the personal information included on the
site by students, such as the potential ability to reconstruct users’ social security
numbers using information often found in profiles, such as hometown and date of
birth.
Acquisti and Gross (2006) argue that there is often a disconnect between stu-
dents’ desire to protect privacy and their behaviors, a theme that is also explored in
Stutzman’s (2006) survey of Facebook users and Barnes’s (2006) description of the
‘‘privacy paradox’’ that occurs when teens are not aware of the public nature of the
Internet. In analyzing trust on social network sites, Dwyer, Hiltz, and Passerini
(2007) argued that trust and usage goals may affect what people are willing to
share—Facebook users expressed greater trust in Facebook than MySpace users
did in MySpace and thus were more willing to share information on the site.
In another study examining security issues and SNSs, Jagatic, Johnson, Jakobsson,
and Menczer (2007) used freely accessible profile data from SNSs to craft a ‘‘phishing’’
scheme that appeared to originate from a friend on the network; their targets were
much more likely to give away information to this ‘‘friend’’ than to a perceived
stranger. Survey data offer a more optimistic perspective on the issue, suggesting that
teens are aware of potential privacy threats online and that many are proactive about
taking steps to minimize certain potential risks. Pew found that 55% of online teens
have profiles, 66% of whom report that their profile is not visible to all Internet users
(Lenhart & Madden, 2007). Of the teens with completely open profiles, 46% reported
including at least some false information.
Privacy is also implicated in users’ ability to control impressions and manage
social contexts. Boyd (in press-a) asserted that Facebook’s introduction of the ‘‘News
Feed’’ feature disrupted students’ sense of control, even though data exposed
through the feed were previously accessible. Preibusch, Hoser, Gürses, and Berendt
(2007) argued that the privacy options offered by SNSs do not provide users with the
flexibility they need to handle conflicts with Friends who have different conceptions
of privacy; they suggest a framework for privacy in SNSs that they believe would help
resolve these conflicts.
SNSs are also challenging legal conceptions of privacy. Hodge (2006) argued that
the fourth amendment to the U.S. Constitution and legal decisions concerning
privacy are not equipped to address social network sites. For example, do police
officers have the right to access content posted to Facebook without a warrant? The
legality of this hinges on users’ expectation of privacy and whether or not Facebook
profiles are considered public or private.
Other Research
In addition to the themes identified above, a growing body of scholarship addresses
other aspects of SNSs, their users, and the practices they enable. For example, schol-
arship on the ways in which race and ethnicity (Byrne, in press; Gajjala, 2007),
222 Journal of Computer-Mediated Communication 13 (2008) 210–230 ª 2008 International Communication Association
religion (Nyland & Near, 2007), gender (Geidner, Flook, & Bell, 2007; Hjorth & Kim,
2005), and sexuality connect to, are affected by, and are enacted in social network
sites raise interesting questions about how identity is shaped within these sites.
Fragoso (2006) examined the role of national identity in SNS use through an inves-
tigation into the ‘‘Brazilian invasion’’ of Orkut and the resulting culture clash
between Brazilians and Americans on the site. Other scholars are beginning to do
cross-cultural comparisons of SNS use—Hjorth and Yuji (in press) compare Japa-
nese usage of Mixi and Korean usage of Cyworld, while Herring et al. (2007) examine
the practices of users who bridge different languages on LiveJournal—but more work
in this area is needed.
Scholars are documenting the implications of SNS use with respect to schools,
universities, and libraries. For example, scholarship has examined how students feel
about having professors on Facebook (Hewitt & Forte, 2006) and how faculty par-
ticipation affects student-professor relations (Mazer, Murphy, & Simonds, 2007).
Charnigo and Barnett-Ellis (2007) found that librarians are overwhelmingly aware of
Facebook and are against proposed U.S. legislation that would ban minors from
accessing SNSs at libraries, but that most see SNSs as outside the purview of librar-
ianship. Finally, challenging the view that there is nothing educational about SNSs,
Perkel (in press) analyzed copy/paste practices on MySpace as a form of literacy
involving social and technical skills.
This overview is not comprehensive due to space limitations and because much
work on SNSs is still in the process of being published. Additionally, we have not
included literature in languages other than English (e.g., Recuero, 2005 on social
capital and Orkut), due to our own linguistic limitations.
Overview of This Special Theme Section
The articles in this section address a variety of social network sites—BlackPlanet,
Cyworld, Dodgeball, Facebook, MySpace, and YouTube—from multiple theoretical
and methodological angles, building on previous studies of SNSs and broader the-
oretical traditions within CMC research, including relationship maintenance and
issues of identity, performance, privacy, self-presentation, and civic engagement.
These pieces collectively provide insight into some of the ways in which online
and offline experiences are deeply entwined. Using a relational dialectics approach,
Kyung-Hee Kim and Haejin Yun analyze how Cyworld supports both interpersonal
relations and self-relation for Korean users. They trace the subtle ways in which
deeply engrained cultural beliefs and activities are integrated into online communi-
cation and behaviors on Cyworld—the online context reinforces certain aspects of
users’ cultural expectations about relationship maintenance (e.g., the concept of
reciprocity), while the unique affordances of Cyworld enable participants to over-
come offline constraints. Dara Byrne uses content analysis to examine civic engage-
ment in forums on BlackPlanet and finds that online discussions are still plagued
with the problems offline activists have long encountered. Drawing on interview and
Journal of Computer-Mediated Communication 13 (2008) 210–230 ª 2008 International Communication Association 223
observation data, Lee Humphreys investigates early adopters’ practices involving
Dodgeball, a mobile social network service. She looks at the ways in which networked
communication is reshaping offline social geography.
Other articles in this collection illustrate how innovative research methods can
elucidate patterns of behavior that would be indistinguishable otherwise. For
instance, Hugo Liu examines participants’ performance of tastes and interests by
analyzing and modeling the preferences listed on over 127,000 MySpace profiles,
resulting in unique ‘‘taste maps.’’ Likewise, through survey data collected at a college
with diverse students in the U.S., Eszter Hargittai illuminates usage patterns that
would otherwise be masked. She finds that adoption of particular services correlates
with individuals’ race and parental education level.
Existing theory is deployed, challenged, and extended by the approaches adopted
in the articles in this section. Judith Donath extends signaling theory to explain
different tactics SNS users adopt to reduce social costs while managing trust and
identity. She argues that the construction and maintenance of relations on SNSs is
akin to ‘‘social grooming.’’ Patricia Lange complicates traditional dichotomies
between ‘‘public’’ and ‘‘private’’ by analyzing how YouTube participants blur these
lines in their video-sharing practices.
The articles in this collection highlight the significance of social network sites
in the lives of users and as a topic of research. Collectively, they show how
networked practices mirror, support, and alter known everyday practices, espe-
cially with respect to how people present (and hide) aspects of themselves and
connect with others. The fact that participation on social network sites leaves
online traces offers unprecedented opportunities for researchers. The scholarship
in this special theme section takes advantage of this affordance, resulting in work
that helps explain practices online and offline, as well as those that blend the two
environments.
Future Research
The work described above and included in this special theme section contributes to
an on-going dialogue about the importance of social network sites, both for practi-
tioners and researchers. Vast, uncharted waters still remain to be explored. Meth-
odologically, SNS researchers’ ability to make causal claims is limited by a lack of
experimental or longitudinal studies. Although the situation is rapidly changing,
scholars still have a limited understanding of who is and who is not using these
sites, why, and for what purposes, especially outside the U.S. Such questions will
require large-scale quantitative and qualitative research. Richer, ethnographic research
on populations more difficult to access (including non-users) would further aid
scholars’ ability to understand the long-term implications of these tools. We hope
that the work described here and included in this collection will help build a foun-
dation for future investigations of these and other important issues surrounding
social network sites.
224 Journal of Computer-Mediated Communication 13 (2008) 210–230 ª 2008 International Communication Association
Acknowledgments
We are grateful to the external reviewers who volunteered their time and expertise to
review papers and contribute valuable feedback and to those practitioners and ana-
lysts who provided information to help shape the history section. Thank you also to
Susan Herring, whose patience and support appeared infinite.
Notes
1 To differentiate the articulated list of Friends on SNSs from the colloquial term
‘‘friends,’’ we capitalize the former.
2 Although one out of seven teenagers received unwanted sexual solicitations online, only
9% came from people over the age of 25 (Wolak, Mitchell, & Finkelhor, 2006). Research
suggests that popular narratives around sexual predators on SNSs are misleading—
cases of unsuspecting teens being lured by sexual predators are rare (Finkelhor, Ybarra,
Lenhart, boyd, & Lordan, 2007). Furthermore, only .08% of students surveyed by the
National School Boards Association (2007) met someone in person from an online
encounter without permission from a parent.
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About the Authors
danah m. boyd is a Ph.D. candidate in the School of Information at the University of
California-Berkeley and a Fellow at the Harvard University Berkman Center for
Internet and Society. Her research focuses on how people negotiate mediated con-
texts like social network sites for sociable purposes.
Address: 102 South Hall, Berkeley, CA 94720–4600, USA
Nicole B. Ellison is an assistant professor in the Department of Telecommunication,
Information Studies, and Media at Michigan State University. Her research explores
issues of self-presentation, relationship development, and identity in online environ-
ments such as weblogs, online dating sites, and social network sites.
Address: 403 Communication Arts and Sciences, East Lansing, MI 48824, USA
230 Journal of Computer-Mediated Communication 13 (2008) 210–230 ª 2008 International Communication Association
Computers in Human Behavior 27 (2011) 1152–1161
Contents lists available at ScienceDirect
Computers in Human Behavior
j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / c o m p h u m b e h
Why people use social networking sites: An empirical study integrating
network externalities and motivation theory
Kuan-Yu Lin ⇑, Hsi-Peng Lu
Department of Information Management, National Taiwan University of Science and Technology, No. 43 Keelung Road, Sec. 4, Taipei 106, Taiwan, ROC
a r t i c l e i n f o
Article history:
Available online 22 January 2011
Keywords:
Continued intention to use
Motivation theory
Network externalities
Perceived benefit
Social networking site
0747-5632/$ – see front matter � 2010 Elsevier Ltd. A
doi:10.1016/j.chb.2010.12.009
⇑ Corresponding author. Tel.: +886 2 2737 6764; fa
E-mail addresses: ntustmislab@gmail.com (K.-Y. Li
P. Lu).
a b s t r a c t
Fast-developing social networking sites (SNS) have become the major media by which people develop
their personal network online in recent years. To explore factors affecting user’s joining SNS, this study
applies network externalities and motivation theory to explain why people continue to join SNS. This
study used an online questionnaire to conduct empirical research, and collected and analyzed data of
402 samples by structural equation modeling (SEM) approach. The findings show that enjoyment is
the most influential factor in people’s continued use of SNS, followed by number of peers, and usefulness.
The number of peers and perceived complementarity have stronger influence than the number of mem-
bers on perceived benefits (usefulness and enjoyment). This work also ran clustering analysis by gender,
which found notable difference in both number of peers and number of members between men and
women. The number of peers is an important factor affecting the continued intention to use for women
but not for men; the number of members has no significant effect on enjoyment for men. The findings
suggest that gender difference also produces different influences. The implication of research and discus-
sions provides reference for SNS operators in marketing and operation.
� 2010 Elsevier Ltd. All rights reserved.
1. Introduction 2009). Users who propagate perceived benefit of use to their
Social networking sites (SNS) have infiltrated people’s daily life
with amazing rapidity to become an important social platform for
computer-mediated communication (Correa, Hinsley, & de Zuniga,
2010; Powell, 2009; Tapscott, 2008). Facebook, MySpace, and
Friendster are successful examples (Kang & Lee, 2010; Lipsman,
2007; Pempek, Yermolayeva, & Yermolayeva, 2009). SNS, by defini-
tion, provides a new method of communicating, employing com-
puters as a collaborative tool to accelerate group formation and
escalate group scope and influence (Kane, Fichman, Gallaugher, &
Glaser, 2009; Pfeil, Arjan, & Zaphiris, 2009; Ross et al., 2009). The
SNS innovative operation mode has not only successfully drawn
the attention of industry and academia, but has also boosted user
growth. SNS is currently the world’s fastest developing personal
networking tool.
SNS is a cyber environment that allows the individual to con-
struct his/her profile, sharing text, images, and photos, and to link
other members of the site by applications and groups provided on
the Internet (Boyd & Ellison, 2008; Pfeil et al., 2009; Powell, 2009;
Tapscott, 2008). Hence, SNS enables users to present themselves,
connect to a social network, and develop and maintain relation-
ships with others (Ellison, Steinfield, & Lampe, 2007; Kane et al.,
ll rights reserved.
x: +886 2 2737 6777.
n), lu@mail.ntust.edu.tw (H.-
friends and relatives achieve network externalities, and positive
feedback gives rise to larger expansion, which increases platform
members (Powell, 2009). Facebook is an obvious example. Face-
book statistics indicate that its global members have rapidly in-
creased from 150 million to about 350 million between January
and December 2009 (Eldon, 2009). Hence, network externalities
not only increase its economic benefits, but also have significant
effect on expanding social network potential.
The above reveals that network externalities are an important
factor affecting Internet users, a reason for people to use informa-
tion technology (Gupta & Mela, 2008; Schmitz & Latzer, 2002).
However, previous research has seldom studied how network
externalities relate to the formation of user’s perception about
SNS. In addition, as the SNS spirit emphasizes user’s interaction
and involvement, users are the key to a successful website (Powell,
2009; Sledgianowski & Kulviwat, 2009). Thus, ‘‘what motives affect
continued intention to use’’ becomes an important issue. Many
researchers (Davis, Bagozzi, & Warshaw, 1992; Igbaria, Parasur-
aman, & Baroudi, 1996; Lin & Bhattacherjee, 2008; Teo, Lim, &
Lai, 1999; van der Heijden, 2004) have recently explicated individ-
ual’s behavior of using information technology from the motiva-
tion theory perspective. They discovered that both internal and
external motivations influenced such behavioral intention,
whereas, the benefits perceived by individuals was derived from
the factor of motivation (Kim, Chan, & Gupta, 2007). In other
words, the individual adopts information technology because
http://dx.doi.org/10.1016/j.chb.2010.12.009
mailto:ntustmislab@gmail.com
mailto:lu@mail.ntust.edu.tw
http://dx.doi.org/10.1016/j.chb.2010.12.009
http://www.sciencedirect.com/science/journal/07475632
http://www.elsevier.com/locate/comphumbeh
K.-Y. Lin, H.-P. Lu / Computers in Human Behavior 27 (2011) 1152–1161 1153
he/she perceives the possibility of obtaining utility and enjoyment
from it (Kim et al., 2007; Lin & Bhattacherjee, 2008; Lu & Su, 2009;
Moon & Kim, 2001; Teo et al., 1999; van der Heijden, 2004).
SNS service providers need to investigate the correlation be-
tween network externalities and individual motives to compre-
hend the concerns of users to attract them. This study combines
network externalities and motivation theory, to propose a rational
research model to explain why people continue to join the SNS.
Profitable online service performance depends on understanding
users factors of use. Yet, few studies have investigated these fac-
tors. The findings of this study could serve as a reference for SNS
providers for the enhancement of the services they offer.
2. Theoretical background
2.1. Motivation theory
Previous research has widely used motivation theory to explain
individual’s behavior of accepting information technology. Deci
(1975) divided the motivations underlying individual’s behavior
into extrinsic motivation and intrinsic motivation. Extrinsic motiva-
tion refers to committing an action because of its perceived helpful-
ness in achieving value (e.g., the performance of improvement),
while intrinsic motivation refers to committing an action because of
interest in the action itself, rather than external reinforcement (Da-
vis et al., 1992).
Davis et al. (1992) found that both extrinsic (usefulness) and
intrinsic (enjoyment) factors affect the motivation to use informa-
tion technology systems. Later studies (Kim et al., 2007; Lin &
Bhattacherjee, 2008; Lu & Su, 2009; Moon & Kim, 2001; Teo
et al., 1999; van der Heijden, 2004) also found usefulness to be
an extrinsic motivation, and perceived enjoyment an intrinsic
motivation. These two motivations affect the individual’s intention
to use information technology. Kim et al. (2007) pointed out that
perceived benefit affects the individual’s use of information tech-
nology, consisting of cognitive benefit and affective benefit, i.e.,
of extrinsic and intrinsic factors. Based on these reasons, this work
proposes extrinsic benefit (usefulness) and intrinsic benefit (enjoy-
ment) as the components of individual’s perceived benefit in SNS.
2.2. Network externalities
Katz and Shapiro (1985) defined network externalities as ‘‘the va-
lue or effect that users obtain from a product or service will bring
about more values to consumers with the increase of users, com-
plementary product, or service.’’ Hence, once the scale of users
reaches a critical number, external benefit emerges and attracts
more users to join (Lin & Bhattacherjee, 2008). For instance, when
the number of cell phone users reaches a critical mass, it generates
relative benefit, providing subsequent users with more correspon-
dents and a wider scope of use, as well as attracting third-party
businesses (e.g., software developer) to join, which in turn bring
in more users by making cell phone use easier and more conve-
nient. As such, the number of users and availability of complemen-
tary goods or services are factors that drive network externalities.
Many researchers (Gupta & Mela, 2008; Katz & Shapiro, 1985;
Lin & Bhattacherjee, 2008) have pointed out the two types of net-
work externalities: direct and indirect. Direct network externalities
derive from the increase in users of a particular product or service,
where user’s benefits increase. Taking online auction sites as an
example, the more users that buy and sell, the more chances to
choose from there are, and the higher the transaction value is
(Gupta & Mela, 2008). Many researchers (Gupta & Mela, 2008; Iimi,
2005; Kim, Park, & Oh, 2008; Pae & Hyun, 2002; Wu, Chen, & Lin,
2007; Yang & Mai, 2010) have claimed that utility for users is
derived from market size, impacting the way that people use tele-
com facilities, computer software, and websites. For example in the
marketplace, different kinds of people can use these products,
thereby increasing utility for users. This in turn encourages them
to continue using these products and services. On the other hand,
indirect network externalities display an increased sense of user va-
lue from using a product or service, as the effect the user obtains
from such product or service increases with the increase of related
complementary products. The computer software spreadsheet is
an example: consumers are willing to buy or use it to obtain net-
work externalities rising from compatibility (Gandal, 1994). From
the viewpoint of above-mentioned researchers, direct network
externalities are due to the demand side of the network, while
indirect network externalities are the supply side.
Findings from previous research show that researchers have
distinct perspectives about sources of network externalities (as Ta-
ble 1 shows). This investigation found that one single construct too
often represented network externalities, a measurement incapable
of reflecting sources of network externalities commonly consid-
ered in the literature. A number of researchers (Gupta & Mela,
2008; Katz & Shapiro, 1985; Lin & Bhattacherjee, 2008) have indi-
cated the two types of direct and indirect network externalities as
sources of network externalities, thus the measurement in one sin-
gle construct is insufficient. In addition, a number of researchers
(Lin & Bhattacherjee, 2008, 2009) believed that the utility for users
also comes from social effects. In the case of instant messaging
(e.g., MSN Messenger), the more friends that join the network,
the more users can maintain or develop their individual social cir-
cles, thereby increasing the utility for users. Sledgianowski and
Kulviwat (2009) argued that SNS is a pleasure-oriented informa-
tion system that the individual becomes more willing to use as
more friends or peers join (Baker & White, 2010; Li & Bernoff,
2008; Powell, 2009; Tapscott, 2008). Combining these perspec-
tives, this study posits that in the context of a pleasure-oriented
information system, peer network externality is one of the sources
of network externalities. In summarizing the above-stated views
of researchers (Baker & White, 2010; Gupta & Mela, 2008; Katz &
Shapiro, 1985; Li & Bernoff, 2008; Lin & Bhattacherjee, 2008; Pow-
ell, 2009; Sledgianowski & Kulviwat, 2009; van der Heijden, 2004),
this study concluded that in the environment of SNS, the sources of
direct, peer and indirect network externalities should all be consid-
ered with regard to network externalities. Hence, these sources of
network externalities were mentioned in the study to explore their
effects on individual’s continued intention to use SNS.
3. Research model and hypotheses
Fig. 1 presents this study’s research model, developed based on
network externalities and motivation theory. The model considers
that perceived benefits and network externalities are key factors
affecting individual’s continued intention to use, where the com-
posing constructs of perceived benefits are extrinsic benefit (use-
fulness) and intrinsic benefit (enjoyment), while for network
externalities, the model considers three types of sources, namely,
direct (number of members), peer (number of peers), and indirect
(perceived complementarity) network externalities. The figure be-
low presents the definition and hypothesis of each construct.
3.1. Perceived benefits
3.1.1. Extrinsic benefit: usefulness
Davis (1989) defined usefulness as ‘‘the degree to which a person
believes that using a particular system would enhance his or her
job performance,’’ when the individual feels a system is useful,
he or she thinks positively about it. Many scholars (Lee, 2009; Lu,
Table 1
Previous research on network externalities.
Reference Context Source of network externalities
Gandal (1994) Spreadsheets Compatibility effects
Gupta and Mela (2008) Online auction sites Market size effects, Compatibility effects
Iimi (2005) Cellular phone services Market size effects
Kim et al. (2008) Mobile communication service Market size effects
Lin and Bhattacherjee (2009) Online social support Social effects
Lin and Bhattacherjee (2008) Interactive information technologies Compatibility effects, Social effects
Lou et al. (2000) Groupware Social effects
Pae and Hyun (2002) Personal computer operating system Market size effects
Wu et al. (2007) End user computing Market size effects
Yang and Mai (2010) Online video game Market size effects
Fig. 1. The research model.
1154 K.-Y. Lin, H.-P. Lu / Computers in Human Behavior 27 (2011) 1152–1161
Zhou, & Wang, 2009; Pontiggia & Virili, 2010; Sledgianowski &
Kulviwat, 2009; Wu et al., 2007; Yen, Wu, Cheng, & Huang, 2010)
have found that user’s thinking as to the usefulness of a system
had great influence and positively related to adoption of informa-
tion technology. An SNS user cares about whether the SNS allows
him to effectively build and maintain relationships among the
mechanisms that allow strangers to become acquainted and keep
in touch, and that provides for the individual to form profiles and
enable people to reach out toward one another (Li & Bernoff,
2008; Pfeil et al., 2009). Some scholars (Kang & Lee, 2010; Kwon
& Wen, 2010; Sledgianowski & Kulviwat, 2009) have discovered
that users’ perceived usefulness in SNS affects positive intention
to use the SNS. Hence, this work proposes the following
hypotheses:
H1. Usefulness will have a positive effect on continued intention
to use of a social network service.
3.1.2. Intrinsic benefit: enjoyment
Moon and Kim (2001) defined enjoyment as ‘‘the pleasure the
individual feels objectively when committing a particular behavior
or carrying out a particular activity’’ and found in their study that
enjoyment is a key factor for user’s acceptance of the Internet. Da-
vis et al. (1992) incorporated intrinsic motivation in the discussion
about Technology Acceptance Model (TAM) and believed the
intrinsic enjoyment a user obtains from using computer technol-
ogy to engage in work related behavior also promotes behavior
intention. van der Heijden (2004) further pointed out that per-
ceived enjoyment is an important factor in predicting the intention
to use a pleasure-oriented information system. Many scholars
(Kang & Lee, 2010; Sledgianowski & Kulviwat, 2009) have consid-
ered SNS as a pleasure-oriented information system, where users
continue use with stronger motivation if they have more intense
perceived enjoyment from it. Therefore, this study hypothesizes:
H2. Enjoyment will have a positive effect on continued intention
to use of a social network service.
3.2. Network externalities
3.2.1. Using network externalities to explain continued intention to use
Research has considered network externalities an important
factor directly affecting customer’s behavior of using information
technology (Gupta & Mela, 2008; Kim & Lee, 2007; Pae & Hyun,
2002; Schmitz & Latzer, 2002; Yang & Mai, 2010). Sledgianowski
and Kulviwat (2009) believed that a user intends to use an SNS
once its participants reach a significant number. The number of
members of SNS is similar to the install base referred to in prior net-
work studies. The current study uses it to represent direct network
externalities. Peer network externalities refers to the number of
friends who are using, which is a major factor affecting people’s
intention to join SNS, as the SNS design is for the purpose of letting
the acquainted keep in touch, especially when they are allowed to
share with their friends at any time (Baker & White, 2010; Li & Ber-
noff, 2008; Powell, 2009; Tapscott, 2008). Hence, this work uses
the number of peers to represent peer network externalities. A
number of researchers (Gandal, 1994; Shurmer, 1993) have
pointed out that the degree to which users perceive complemen-
tary items or services (e.g., related soft- or hardware support or re-
lated tutorial books) influences their intention to use such
K.-Y. Lin, H.-P. Lu / Computers in Human Behavior 27 (2011) 1152–1161 1155
computer software. An SNS provides many complementary ser-
vices for users to engage in various social applications on the web-
site. One example is social games; examples of supporting tools are
photo sharing, message sharing, and video sharing; an example of
social activities is fan pages; and an example of friend searching
tools is e-mail. These services help to increase the actual availabil-
ity of complementary products perceived by users and further en-
hance users’ continued intention to use (Powell, 2009; Tapscott,
2008). This study uses perceived complementarity to represent indi-
rect network externalities. Summarizing the above arguments, this
work proposes the following hypotheses:
H3a. Number of members will have a positive effect on continued
intention to use of a social network service.
H4a. Number of peers will have a positive effect on continued
intention to use of a social network service.
H5a. Perceived complementarity will have a positive effect on
continued intention to use of a social network service.
3.2.2. Relationship between network externalities and perceived
benefit
Some researchers (Katz & Shapiro, 1985; Lin & Bhattacherjee,
2008) have argued that network externalities affect user’s per-
ceived benefits. When users use a product or service, the increase
in user’s effect not only stems from the number of users, but also
enhances the benefit with the increase of other compatible and
complementary products or services. The best appeal of SNS is its
capability of building trusted relationships outside traditional so-
cial circles (Li & Bernoff, 2008; Powell, 2009; Sledgianowski &
Kulviwat, 2009). Users who continue to contact their friends and
those on extended SNS via SNS’s like Facebook, Myspace, and per-
sonal blogs, affect more people affected, as the website gains mem-
bers (Kane et al., 2009; Li & Bernoff, 2008; Sledgianowski &
Kulviwat, 2009). Thus, when users perceive more members joining
SNS, more people can help them become acquainted with those
outside their individual network, further expanding their connec-
tions (e.g., Fans page), and finding more enjoyment by interacting
and sharing messages with more members (Li & Bernoff, 2008;
Powell, 2009; Tapscott, 2008).
Thus, we hypothesize that:
H3b. Number of members will have a positive effect on usefulness
of a social network service.
H3c. Number of members will have a positive effect on enjoyment
of a social network service.
Users on most SNS normally do not aim to make new friends.
Instead, they link their social networks in real life online to make
further contacts (Boyd & Ellison, 2008); hence, greater numbers
of peers in SNS helps to connect to more mutual friends (e.g., friend
recommendation mechanism) and interaction and sharing be-
tween more friends creates a greater sense of pleasure (Powell,
2009; Tapscott, 2008). Consequently, we hypothesize that:
H4b. Number of peers will have a positive effect on usefulness of a
social network service.
H4c. Number of peers will have a positive effect on enjoyment of a
social network service.
When indirect network externalities refer to a product or ser-
vice with more complementary products or services, it creates
higher benefit and more demand (Lin & Bhattacherjee, 2008). Thus,
for SNS, more complementary products (e.g., supporting tools) help
users to show themselves and maintain interaction with others,
thereby giving users more pleasure (Powell, 2009; Tapscott,
2008). For instance, users can take advantage of photos sharing,
message sharing, and video sharing by using the supporting tools
provided on the websites, to show themselves, share information,
and interact with their friends in various ways. According, we
hypothesize that:
H5b. Perceived complementarity will have a positive effect on
usefulness of a social network service.
H5c. Perceived complementarity will have a positive effect on
enjoyment of a social network service.
4. Research methods
4.1. Data collection and sampling
The current research targets subjects who are users of Taiwan
Facebook (http://zh-tw.facebook.com/), currently the third most
popular website in Taiwan, according to Alexa.com (Alexa, 2010)
statistics. Facebook was created by Mark Zuckerberg in February
4, 2004, initially intended for use only by students at Harvard Uni-
versity to share their status, photos, and other details with school-
mates via a network. It gradually expanded to become an SNS
across US universities until it assumed global proportions (Powell,
2009). Since June 2008, it has been providing web pages in Chinese
for Taiwanese users. As such, the online platforms of Facebook in
Taiwan and the US differ only in the language interface, while
the services they provide are similar. Thanks to the availability of
the Chinese version, the number of Facebook users in Taiwan has
been growing rapidly. Statistics by CheckFacebook.com (2010)
pointed out that the number of Taiwan users in September 2009
accounted for only 1.04% of the world’s users, a growth rate of
26.69%, ranking No. 1 in the world. Taiwan members exceeded
6.5 million in May 2010, making this site the largest SNS in Taiwan.
Therefore, the current investigation chose it as the research
subject.
Online questionnaires gathered data, distributed from January
15 to March 15, 2010 to randomly chosen Facebook users. Mean-
while, this research posted messages about the questionnaire on
websites of Facebook related activities and telnet://ptt.cc, the most
popular bulletin board systems (BBS) in Taiwan. To encourage
respondents to fill out the questionnaire, this project offered gifts,
hoping to reinforce the sample return rate. Respondents’ identity
was checked by their e-mail and IP address, when the question-
naires were received, to avoid replications.
Four hundred and two usable responses were received, of
which, male samples and female samples were nearly equal in
number and the largest age group was 25–34 years, accounting
for 40.5%. Regarding the educational and occupational levels, 51%
of the responders were undergraduates and 53% were students.
Of the three types of services that Facebook provides, communica-
tion (i.e., comment and e-mail) and contents (i.e., games and news)
emerged as the most frequently tried services, followed by com-
merce (i.e., advertisement). Table 2 shows the detailed sample
demographics.
4.2. Measurement development
The questionnaire adapted questionnaire items from previous
literature; Appendix A lists the items. The scale for continued
intention to use was adapted from Kim et al. (2008). The scale
for usefulness was adapted from Davis (1989) and Kwon and
Wen (2010). Enjoyment items were adapted from Agarwal and
http://zh-tw.facebook.com/
Table 2
Sample demographics.
Measure Item Frequency Percentage (%)
Gender Male 204 50.7
Female 198 49.3
Age (years) Under 18 36 9
18–24 129 32.1
25–34 163 40.5
35–44 49 12.2
45–54 21 5.2
>54 4 1
Education High school or under 59 14.7
Undergraduate 205 51
Graduate degree 138 34.3
Occupation Student 213 53
Office worker 149 37.1
Self-employment 11 7.2
Home makers 29 2.7
Facebook servicesa Communications 184 45.8
Contents 197 49
Commerce 21 5.2
a Most frequently tried.
1156 K.-Y. Lin, H.-P. Lu / Computers in Human Behavior 27 (2011) 1152–1161
Karahanna (2000) and Kim et al. (2007). As for the three constructs
of network externalities, direct network externalities, which is the
extent to which the number of SNS users increase, were modified
from Pae and Hyun’s items (Pae & Hyun, 2002). Peer network
externalities, which are the extent to which the number of friends
using SNS the individual thinks will increase, were drawn up with
reference to the measuring items of Lou, Luo, and Strong (2000),
further modified according to the present topic. Indirect network
externalities, which are the degree to which the individual thinks
SNS complementary products or services will increase, were for-
mulated with reference to the scale developed by Lin and Bhatt-
acherjee (2008) and further modified as appropriate. All items
were measured on a five-point Likert-type scale, ranging from ‘‘dis-
agree strongly’’ (1) to ‘‘agree strongly’’ (5).
Both a pre-test and a pilot test were used to validate the instru-
ment. The pre-test involved seven respondents, each with more
than 2 years of experience using SNS. Respondents were asked to
comment on the length of the instrument, the format, and the
wording of the scales. The pilot test involved fifty respondents
self-selected from the Facebook population. Based on respondents’
feedback at the pre-test and pilot test, several questionnaire items
were modified to reflect more clearly the survey’s purpose. The
reliability for all items was satisfactory (Cronbach’s alpha above
0.80) and items loaded in the correct factors in confirmatory factor
analysis (with loadings of 0.60 or more). Therefore, the instrument
has confirmed content validity and reliability. A list of the pilot test
data is displayed in Appendix B.
5. Results
Data analysis followed the two-step approach by Anderson and
Gerbing (1988), to test convergent validity and discriminant
Table 3
Fit indices for the Measurement models.
Fit Indices Recommended val
v2/df 53
Goodness of fit index (GFI) =0.9
Adjusted for degrees of freedom (AGFI) =0.8
Normed fit index (NFI) =0.9
Comparative fit index (CFI) =0.9
Root mean square error of approximation (RMSEA) 50.08
validity of the measurement model, followed by testing the re-
search hypotheses and structural model framework.
5.1. Tests of the measurement model
Confirmatory factor analyses (CFA) used AMOS 7.0 for testing
the measurement model. Hair, Anderson, Tatham, and Black
(1998) argued that most model-fit indices should reach accepted
standards before judging model fitness. Table 3 shows that every
model-fit index exceeded the recommended value from previous
studies, exhibiting an adequate fit to the collected data.
Reliability analysis used Cronbach’s alpha and composite reli-
ability, CR, to assess the model’s internal consistency. Table 4
shows the results. The Cronbach’s alpha of each construct ranged
from 0.82 to 0.91, i.e., greater than the accepted level of 0.7 recom-
mended by Nunnally (1978). Every CR scored above 0.8, which ex-
ceeded 0.7 suggested for CRs by Fornell and Larcker (1981),
indicating good reliability and stability for the measurement items
of each construct.
Convergent validity used the three standards recommended
by Bagozzi and Yi (1988) to assess the measuring model: (1) all
indicator factor loadings should exceed 0.5 (Hair et al., 1998);
(2) CR should be above 0.7; and (3) the average variance ex-
tracted, AVE, of every construct should exceed 0.5 (Fornell & Lar-
cker, 1981). As Table 4 shows, the indicator factor loading of
every item in the measuring model of this study exceeded 0.7.
Composite reliability of constructs ranged from 0.83 to 0.91.
AVE ranged from 0.59 to 0.77, therefore meeting all conditions
for convergent validity.
In discriminant validity, as Fornell and Larcker (1981) sug-
gested, the AVE of construct should exceed other correlation coef-
ficients of the construct. Table 5 shows the matrix of correlation
coefficients for all constructs in this research. Diagonal elements
are the square roots of average variance extracted for the con-
structs. The correlation coefficients between any two constructs
are smaller than the square root of the average variance extracted
for the constructs. Constructs in the measurement model of this re-
search indeed are different from one another, indicating that all
constructs in this research carry sufficient discriminant validity.
Therefore, the measurement model in this research shows satisfac-
tory reliability, convergent validity, and discriminant validity.
5.2. Tests of the structural model
The current research tested the structural model using AMOS
7.0. The model-fit indices for the structural model provided evi-
dence of a good model fit (v2/df = 1.96, GFI = 0.94, AGFI = 0.91,
NFI = 0.95, CFI = 0.97, RMSEA = 0.049). Fig. 3 displays the standard-
ized path coefficients, path significances, and variance explained
(R2) by each path, all supported by the path analysis results, except
H3a, H3c, and H5a. As with variance explained (R2), R2 of continued
intention to use reached 69% and that of usefulness 58%, and that
of enjoyment 60%. R2 of every latent dependent variable was over
0.5, suggesting good explanatory power for the research model.
Apart from the test of total model fit and the evaluation of
intrinsic model quality, when explaining the model, it is necessary
ue Suggested by authors Measurement model
Hayduck (1987) 1.86
Scott (1991) 0.94
Scott (1991) 0.92
Bentler and Bonett (1980) 0.95
Bagozzi and Yi (1988) 0.97
Bagozzi and Yi (1988) 0.046
Table 4
Statistics of construct items.
Construct Items Factor loadings t-Statistic Composite reliability (CR) Average variance extracted (AVE) Alpha
Number of members NM1 0.77 0.83 0.61 0.82
NM2 0.88 14.93
NM3 0.69 12.86
Number of peers NP1 0.85 0.86 0.68 0.86
NP2 0.81 19.13
NP3 0.81 18.29
Perceived complementarity PC1 0.79 0.85 0.59 0.85
PC2 0.83 17.23
PC3 0.74 14.80
PC4 0.70 13.81
Usefulness USE1 0.84 0.86 0.67 0.85
USE2 0.90 20.88
USE3 0.70 15.10
Enjoyment ENJ1 0.89 0.91 0.77 0.91
ENJ2 0.88 24.53
ENJ3 0.87 23.70
Continued intention to use CIU1 0.90 0.87 0.77 0.86
CIU2 0.85 20.35
Table 5
Discriminant validity.
Construct NM NP PC USE ENJ CIU
NM 0.78
NP 0.39 0.82
PC 0.31 0.53 0.77
USE 0.41 0.61 0.54 0.82
ENJ 0.39 0.64 0.57 0.60 0.88
CIU 0.40 0.63 0.54 0.58 0.70 0.88
Note: NM (number of members); NP (number of peers); PC (perceived comple-
mentarity); USE (usefulness); ENJ (enjoyment); CIU (continued intention to use).
Diagonal elements (bold) are the square root of average variance extracted (AVE)
between the constructs and their measures. Off-diagonal elements are correlations
between constructs. For discriminant validity, diagonal elements should be larger
than off-diagonal elements. All correlations are significant at p < 0.01.
K.-Y. Lin, H.-P. Lu / Computers in Human Behavior 27 (2011) 1152–1161 1157
to compare standardized direct, indirect, and total effects of the
model before understanding the correlation between the variables.
First, usefulness (b = 0.16, p < 0.05) and enjoyment (b = 0.44,
p < 0.001) had positive direct effects on continued intention to
use. Second, through usefulness (b = 0.14, p < 0.01), the number
of members (direct network externalities) had positive indirect ef-
fect on continued intention to use, where indirect effect was 0.02
(=0.14 � 0.16). Third, the number of peers (peer network external-
ities) (b = 0.21, p < 0.01) had positive direct effect on continued
intention to use and, both usefulness (b = 0.46, p < 0.001) and
enjoyment (b = 0.50, p < 0.001), had positive indirect effect on con-
tinued intention to use, resulting in the combined effect of 0.50
(=0.21 + 0.46 � 0.16 + 0.50 � 0.44). Finally, perceived complemen-
tarity (indirect network externalities) through both usefulness
(b = 0.30, p < 0.001) and enjoyment (b = 0.31, p < 0.001) had posi-
tive indirect effect on continued intention to use, which indirect ef-
fect was 0.18 (=0.30 � 0.16 + 0.31 � 0.44). Unfortunately, neither
the direct effect of the number of members (b = 0.06, p > 0.05)
nor that of perceived complementarity (b = 0.10, p > 0.05) met
the significant level; this suggested that the number of members
increased user’s continued intention to use only through useful-
ness as a mediator. Further, we found that in the effect of the num-
ber of peers on continued intention to use, the indirect effect
through enjoyment was (0.22) > (0.21) of direct effect. The results
of this study indicate that network externalities effectively in-
crease user’s continued intention to use only through usefulness
and enjoyment as a mediator.
5.3. Difference between men and women
Acceptance analysis for new information technology often uses
gender difference, among all personality features (Sanchez-Franco,
2006; Venkatesh & Morris, 2000) mainly men and women have dif-
ferent views for measuring value and benefit (Gefen & Straub, 1997;
Venkatesh & Morris, 2000). This study thus uses the AMOS 7.0 Multi-
ple-Group Analysis to understand whether male and female subjects
(204 male and 198 female) have difference in the cause and effect of
the model constructs in this study. The indices of fit for the two
groups are consistent with the suggested values by other researchers
(v2/df = 1.63, GFI = 0.91, AGFI = 0.87, NFI = 0.92, CFI = 0.97,
RMSEA = 0.04), thus entitling us to verify a high degree of goodness
of fit between the model and the sample data.
Fig. 3 (for men) and Fig. 4 (for women) show the estimates of
path coefficients and the results of variance explained (R2) between
the constructs. The results indicate that gender groups have signif-
icant difference in the path ‘‘number of peers ? continued inten-
tion to use’’ and the path ‘‘number of members ? enjoyment’’.
On continued intention to use, both usefulness and enjoyment in
men have direct influence, while enjoyment, usefulness, and num-
ber of peers in women all have direct influence. On the benefit of
network externalities, except for number of members in men,
which does not affect enjoyment, all have significant effects. In wo-
men, all three sources of network externalities significantly relate
to perceived benefit. This study infers that women are more sus-
ceptible to peer influence in using SNS, while men are not. Compar-
isons show that men are more rational and less susceptible to
empathy, so usefulness and enjoyment are more important to
them.
6. Discussion
6.1. Correlations between users and network externalities, perceived
benefit, and continued intention to use
This paper sheds light on why people continue to use SNS. The
present research combines the network externalities theory and
motivation theory to discover why people join SNS. The research
results found that network externalities, usefulness, and enjoy-
ment all play important roles in why people join SNS.
Fig. 2 shows the complete research results on all users. First, in
the influence on user’s intention to join SNS, enjoyment has
Fig. 2. Path analysis result based on all valid samples (n = 402).
Fig. 3. Path analysis result for men samples (n = 204).
Fig. 4. Path analysis result for women samples (n = 198).
1158 K.-Y. Lin, H.-P. Lu / Computers in Human Behavior 27 (2011) 1152–1161
K.-Y. Lin, H.-P. Lu / Computers in Human Behavior 27 (2011) 1152–1161 1159
stronger significant effect on people’s continued use of SNS. The re-
sult, consistent with studies by many researchers (Kang & Lee,
2010; Lin & Bhattacherjee, 2008; Sledgianowski & Kulviwat,
2009; van der Heijden, 2004), suggests that in the context of a
pleasure-oriented information system, enjoyment plays an impor-
tant role. Second, in the number of peers (peer network externali-
ties), users essentially connect with old friends on Facebook
(Ellison et al., 2007), and most users’ interactions via SNS are fre-
quently with friends in off-line, real-world life (Pempek et al.,
2009). User’s continued intention to use SNS intensifies when the
user perceives many friends using SNS and anticipates more
friends joining SNS in the future (Baker & White, 2010). Last, the
positive influence of usefulness on continued intention to use
SNS indicates that user’s continued intention to use SNS elevates
when the user believes SNS upgrades the efficiency of his informa-
tion sharing and connecting with others, or enables him to know
more people (Kwon & Wen, 2010). The research result also ap-
proves of van der Heijden (2004) perspective, that when predicting
a pleasure-type information system, perceived enjoyment is an
appropriate factor, whereas perceived usefulness is more for a
task-oriented information system. Clearly, creating an enjoyable
environment for interaction for pleasure-oriented SNS might be
more effective than emphasizing utilitarian benefits.
The number of peers (peer network externalities) and perceived
complementarity (indirect network externalities) are more influ-
ential on extrinsic benefit (usefulness) than the number of mem-
bers (direct network externalities). This finding suggests that the
individual strongly believes that the breadth of his friends using
SNS is great (Baker & White, 2010) or when complementary re-
sources such as various supporting tools, applications, and groups
of social connections are diverse (Lin & Bhattacherjee, 2008), the
degree of SNS usefulness is naturally higher (e.g., broader circle
of friends and more interactions). Similarly, the number of peers
and perceived complementarity predict intrinsic benefit (enjoy-
ment), suggesting that with increased peer connections and com-
plementary tools, SNS interaction becomes more interesting.
However, another index, the number of members, has no signifi-
cant effect on enjoyment; this might be because SNS builds indi-
vidual-centered networks and forms self-centered groups (Boyd
& Ellison, 2008), where, despite a critical legion of users, it is diffi-
cult to arouse an enjoyable mood in a user if he lacks development
and connection with others. Hence, SNS service providers can en-
hance interactions and exchanges between people with the same
interests by sponsoring activities for jazzing up and further arous-
ing user pleasure and fun, to intensify continued intention to use.
6.2. Correlations between gender groups and network externalities,
perceived benefit, and continued intention to use
This study discovered that gender makes a notable difference in
the effect of perceived benefit and network externalities on the
continued intention to use SNS. Figs. 3 and 4 are the results of
structural model analysis with men and women. First, in the paths
of influence on continued intention to use, the number of peers has
significant effect with women, but not with men. Previous research
has found that women are more sensitive to other’s opinions
(Venkatesh & Morris, 2000; Venkatesh, Morris, Davis, & Davis,
2003), and susceptible to the influence of their colleagues and
friends to use a new technology. In contrast, men use new technol-
ogies, as their task requires (Minton & Schneider, 1980). Second, in
the paths of influence on enjoyment, the number of members does
not have significance for men, indicating men do not feel pleasure
with SNS’s with a large number of members; instead, it affects
them in perceiving that expanding their own social circle is useful.
This study found that of all three sources of network externalities,
the number of peers has greatest influence on usefulness and
enjoyment for women, and the number of peers and perceived
complementarity are most influential for men. Therefore, due to
gender difference, different sources of network externalities have
different influences on perceived benefit with SNS.
7. Conclusions
This study proposes an integrated theoretical framework for
academic researchers by combining motivation theory and net-
work externalities to investigate the attitudes and factors of user’s
using SNS, and proposes possible factors of effects to understand
why users continue to use. The study results suggest our research
models exhibit good explanatory power to predict user’s continued
intention to use SNS, providing a new direction for researchers to
contemplate in subsequent research.
Social network service practitioners can draw several implica-
tions from this study. First, the results suggest that enjoyment is
the most important factor affecting the behavior of SNS users
(Sledgianowski & Kulviwat, 2009). By enhancing users’ posting
photos, films, and weblogs, and sharing links on their profiles,
SNS service providers will be able to make users and their friends
feel interested and have fun (Powell, 2009; Tapscott, 2008). In
addition, SNS service providers should continue developing appli-
cations and small games with novel, pleasurable experiences to
reinforce pleasurable effects in using the site and further to
strengthen its stickiness. Second, the results suggest that the num-
ber of peers and perceived complementarity effectively reinforce
SNS usefulness and enjoyment, providing SNS service providers
with important information, that in the context of a pleasure-ori-
ented information system, makes social effects an important con-
struct. A user’s friends and relatives influence the level of user’s
perceived enjoyment in SNS; also, through them, the user has the
opportunity to meet new friends, whereby people can expand their
social network (Li & Bernoff, 2008; Powell, 2009; Sledgianowski &
Kulviwat, 2009; Tapscott, 2008). Practitioners should constantly
incorporate and develop various activities or useful applications
to allow people to reach out to each other, to reinforce user’s enjoy-
ment, increase social connections, and further intensify user’s inten-
tion to use, increasing SNS value. Third, the influences of different
factors on continued use of information technology vary due to gen-
der difference. Enjoyment is the most powerful factor affecting con-
tinued intention to use SNS for both men and women. Among the
reasons for attracting users to continue to use SNS, the ability to
arouse inner pleasure is the crucial one. This research recommends
that SNS operators develop specific applications for the demands
of different genders, and promote users to have friends in their
own social network joining the SNS to develop network externalities
and encourage more people to use such a platform.
Despite its valuable findings and implications, this study con-
tains some limitations. First, the implications are from a single
study with samples in Taiwan. Therefore, research should use cau-
tion when generalizing the findings to other SNS situations. Future
studies should conduct research in cross-cultural and cross-mar-
ketplace contexts to investigate and compare the differences in
antecedents to continued intention to use. Second, this study em-
ployed a quantitative statistics research model and collected data
by means of an online questionnaire; it is thus difficult for repre-
sented research sampling to avoid self-selection. Researchers
should introduce qualitative interview methods for in-depth
understanding of user’s use, to prevent online questionnaire
respondents from casual answering to win prizes. Third, Facebook
functions include providing various applications and socializing
games. Future researchers could investigate whether the use inten-
sity of social games helps expand user’s social network and analyze
user’s use behavior.
1160 K.-Y. Lin, H.-P. Lu / Computers in Human Behavior 27 (2011) 1152–1161
Appendix A
A.1. The questionnaire
A.1.1. Number of members (NM)
NM1 I think a good number of people use
Facebook.
NM2 I think most people are using Facebook.
NM3 I think there will still be many people joining Facebook.
A.1.2. Number of members Peers (NP)
NP1 I think many friends around me use Facebook.
NP2 I think most of my friends are using Facebook.
NP3 I anticipate many friends will use Facebook in the
future.
A.1.3. Perceived complementarity (PC)
PC1 A wide range of applications is available on Facebook.
PC2 A wide range of supporting tools is available on Facebook
(e.g., photo sharing, message sharing, video sharing).
PC3 A wide range of social activities on Facebook can be joined
(e.g., fan pages).
PC4 A wide range of friend-finding tools is available on
Facebook.
A.1.4. Usefulness (USE)
USE1 Using Facebook enables me to acquire more information
or know more people.
USE2 Using Facebook improves my efficiency in sharing infor-
mation and connecting with others.
USE3 Facebook is a useful service for interaction between
members.
A.1.5. Enjoyment (ENJ)
ENJ1 Using Facebook provides me with a lot of enjoyment.
ENJ2 I have fun using Facebook.
ENJ3 Using Facebook bores me (reversed).
A.1.6. Continued intention to use (CIU)
CIU1 I intend to keep using Facebook in the future.
CIU2 I intend to recommend my friends to use Facebook in the
future.
Appendix B
Table B1.
Table B1
Results of confirmatory factor analysis and reliability analysis.
Construct Items Factor loadings Cronbach‘s alpha
Number of members NM1 0.87 0.81
NM2 0.83
NM3 0.60
Number of peers NP1 0.83 0.83
NP2 0.87
NP3 0.70
Perceived complementarity PC1 0.65 0.83
PC2 0.68
PC3 0.73
PC4 0.85
Usefulness USE1 0.73 0.80
USE2 0.65
USE3 0.92
Enjoyment ENJ1 0.82 0.93
ENJ2 0.94
ENJ3 0.93
Continued intention to use CIU1 0.90 0.83
CIU2 0.78
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- Why people use social networking sites: An empirical study integrating network externalities and motivation theory
Introduction
Theoretical background
Motivation theory
Network externalities
Research model and hypotheses
Perceived benefits
Extrinsic benefit: usefulness
Intrinsic benefit: enjoyment
Network externalities
Using network externalities to explain continued intention to use
Relationship between network externalities and perceived benefit
Research methods
Data collection and sampling
Measurement development
Results
Tests of the measurement model
Tests of the structural model
Difference between men and women
Discussion
Correlations between users and network externalities, perceived benefit, and continued intention to use
Correlations between gender groups and network externalities, perceived benefit, and continued intention to use
Conclusions
Appendix A
The questionnaire
Number of members (NM)
Number of members Peers (NP)
Perceived complementarity (PC)
Usefulness (USE)
Enjoyment (ENJ)
Continued intention to use (CIU)
Appendix B
References
Journal of Applied Developmental Psychology
29 (2008
)
420–433
Contents lists available at ScienceDirect
Journal of Applied Developmental Psychology
Online and offline social networks: Use of social networking sites by
emerging adults☆
Kaveri Subrahmanyam a,b,⁎, Stephanie M. Reich c, Natalia Waechter b,d,e, Guadalupe Espinoza b,d
a Department of Psychology, California State University, Los Angeles, United States
b Children’s Digital Media Center, UCLA/CSULA, United States
c Department of Education, University of California, Irvine, United States
d Department of Psychology, UCLA, United States
e Austrian Institute of Youth Research, Vienna, Austria
a r t i c l e i n f o
☆ Natalia Waechter thanks the Austrian Ministry of
Cheng, David Drachman, Cheryl Groskopf, Elaine Hess
Zhu. Thanks also to Hilda Anwyl, Janice Li, Stefanie Ok
⁎ Corresponding author. Department of Psychology
States. Tel.: +1 323 343 2279.
E-mail address: ksubrah@calstatela.edu (K. Subrah
0193-3973/$ – see front matter © 2008 Elsevier Inc. A
doi:10.1016/j.appdev.2008.07.003
a b s t r a c t
Available online 15 August 2008
Social networking sites (e.g., MySpace and Facebook) are popular online communication forms
among adolescents and emerging adults. Yet little is known about young people’s activities on
these sites and how their networks of “friends” relate to their other online (e.g., instant
messaging) and offline networks. In this study, college students responded, in person and
online, to questions about their online activities and closest friends in three contexts: social
networking sites, instant messaging, and face-to-face. Results showed that participants often
used the Internet, especially social networking sites, to connect and reconnect with friends and
family members. Hence, there was overlap between participants’ online and offline networks.
However, the overlap was imperfect; the pattern suggested that emerging adults may use
different online contexts to strengthen different aspects of their offline connections.
Information from this survey is relevant to concerns about young people’s life online.
© 2008 Elsevier Inc. A
ll rights reserved.
Keywords:
Online communication
Interconnection
Intimacy
Friend networks
Emerging adults
1. Introduction
Over the past decade, the communication uses of the Internet have become a very important part of young people’s lives (e.g.,
Gemmill & Peterson, 2006; Jones, 2002; Lenhart & Madden, 2007; Subrahmanyam & Greenfield, 2008). Social networking sites are
the latest online communication tool that allows users to create a public or semi-public profile, create and view their own as well as
other users’ online social networks (boyd & Ellison, 2007a), and interact with people in their networks. Sites such as MySpace and
Facebook have over 100 million users between them, many of them adolescents and emerging adults. Although research on young
people’s use of social networking sites is emerging (e.g., boyd & Ellison, 2007b; Ellison, Steinfield, & Lampe, 2007; Valkenburg,
Peter, & Schouten, 2006), questions remain regarding exactly what young people do on these sites, whom they interact with on
them, and how their social networking site use relates to their other online (such as instant messaging) and offline activities.
Furthermore, because of the potential to interact with known others as well as meet and befriend strangers on these sites, it is
important to study the nature of their online social networks in order to get an understanding of how such online communication
relates to young people’s development. The goals of the present study were to explore emerging adults’ use of social networking
sites for communication and examine the relation between their online and offline social networks.
Science for financial support. We thank the following students for their invaluable research assistance: Roy
, Jennifer Lai, Judith Murray, Tatevik Natanyan, Nina Tran, Erika Zambrano-Morales, Darab Zarrabi and Kim
imura, and Mollie Tobin.
California State University, Los Angeles 5151 State University Drive Los Angeles, CA 90032-8227, United
manyam).
ll rights reserved.
mailto:ksubrah@calstatela.edu
http://dx.doi.org/10.1016/j.appdev.2008.07.003
http://www.sciencedirect.com/science/journal/01933973
421K. Subrahmanyam et al. / Journal of Applied Developmental Psychology 29 (2008) 420–433
1.1. Online communication in development
The communication forums of the Internet are many and varied and include applications such as instant messaging, email, and
chat rooms as well as Internet sites such as blogs, social networking sites, photo and video sharing sites such as YouTube, and
virtual reality environments such as Second Life. Adolescents (Boneva, Quinn, Kraut, Kiesler, & Shklovski, 2006; Gross, 2004) and
young adults in college (Clark, Frith, & Demi, 2004; Gemmill & Peterson, 2006; Jones, 2002) are heavy users of the Internet relative
to the general population, and use it extensively for communication with peers.
To understand the role of online communication in young people’s development we turn to the theoretical proposal that users
of interactive online forums such as chat rooms, blogs, and social networking sites are co-constructing their online environments
(Subrahmanyam & Greenfield, 2008; Subrahmanyam, Šmahel, & Greenfield, 2006). A major implication of the co-construction
model is that online and offline worlds are psychologically connected. Consequently, we expect that users bring people and issues
from their offline worlds into their online ones. This proposal is in contrast to the view that the Internet allows users to present
online selves that are separate and different from their offline ones (e.g., Byam, 1995; McKenna & Bargh, 2000; Turkle, 1995).
Developmental research on young people’s online behavior supports the claim that online and offline worlds may indeed be
connected.
1.1.1. Connectedness between adolescents’ online and offline worlds
Research suggests that adolescents use instant messaging mainly to communicate with offline friends about events in
school, gossip, and the like (Boneva et al., 2006; Gross, Juvonen, & Gable, 2002). In another study of preadolescent and
adolescent youth in the Netherlands, 80% reported using the Internet to maintain existing friendship networks (Valkenburg &
Peter, 2007). There is also a growing body of research regarding cyber bullying that has highlighted the connections between
online and offline worlds. For example, Ybarra, Mitchell, Wolak, and Finkelhor (2006) found that nearly half of the adolescent
Internet users in their study knew the online bully in person before the cyber bullying incident occurred. With regard to social
networking sites, teens, particularly girls, reported using the sites to keep in contact with peers from their offline lives, either to
make plans with friends that they see often or to keep in touch with friends they rarely see (Lenhart & Madden, 2007). The girls
in this study also reported using social networking sites to reinforce pre-existing friendships whereas boys reported using
them to flirt and make new friends.
Adolescents’ developmental concerns include formulating identity, adjusting to sexuality, and establishing intimate relations
with peers and romantic partners (Brown, 2004; Erikson,1959; Weinstein & Rosen,1991), and recent research indicates that they
use online contexts in the service of these important concerns. Two studies of online teen chat rooms that analyzed 12,000
utterances from 1100 participants found that identity presentation (Subrahmanyam et al., 2006), partner selection (Šmahel &
Subrahmanyam, 2007), and sexual comments (Subrahmanyam et al., 2006) were the most frequent kinds of utterances in chat
rooms. A qualitative study showed that American as well as Austrian teenagers used online chat rooms for the development of
their gender and ethnic identity (Waechter, 2005, 2006). A similar mirroring of adolescent developmental issues was found in a
study of another online forum, weblogs that were written by adolescents (Subrahmanyam, Garcia, Harsono, Lin, & Lipana, in
press). Adolescent bloggers adopted usernames and userpictures for self-presentation and used their blog entries for self-
disclosure about their peers and everyday life. They also used their blog entries to create narratives about themselves and to
reflect about the people and events in their lives. Viewing users’ online worlds as psychologically continuous with their offline
ones enables us to start teasing apart the relation between online communication and development. Much of the research in
support of this view has been done on adolescents, and it is an open question whether such connectedness is present among
emerging adults who are in college.
1.1.2. Connectedness between emerging adults’ online and offline worlds
Prior studies as well as recent anecdotal reports indicate that online and offline contexts may be connected among emerging
adults as well. Anderson (2001) suggested that among college students, excessive Internet use might be related to developmental
issues such as establishing new relationships and identity formation. In a longitudinal study of undergraduate Japanese students’
face-to-face (FTF) social networks and mobile/cell phone text message (MPTM) mediated social networks, Igarashi, Takai, and
Yoshida (2005) reported that at two points during the year, there was mutuality between the two networks: 94% of the time at
Time 1 and 98% of the time at Time 2, persons nominated as a friend in participants’ MPTM social networks were also found on
their FTF social networks. Analysis of measures of relationship intimacy led Igarashi et al. to conclude that even at the beginning of
the academic year, participants used MPTM to communicate with intimate FTF friends.
Another indication that emerging adults’ online and offline worlds are connected comes from a qualitative analysis of
autobiographical essays written by young adult college students (Mcmillan & Morrison, 2008). The participants in this study did
not use the Internet for identity exploration but instead used it to solidify their offline identities. Further, the authors concluded
that participants used their online virtual communities to sustain their “real” communities that existed offline, such as using online
tools to plan social events with their offline friends. Also relevant is a recent Los Angeles Times report that a prolific 24-year-old
graffiti tagger called “Buket” was arrested after the police began investigating him when videos of his vandalism were posted on
YouTube and tagger-related blogs (Blankstein, 2008). The point here is that the tagger, a university graduate with an art degree,
used the online context to showcase his offline exploits. Next, we present the unique developmental challenges that emerging
adults face, followed by research relevant to the question of connectedness in the context of social networking sites, the focus of
this paper.
422 K. Subrahmanyam et al. / Journal of Applied Developmental Psychology 29 (2008) 420–433
1.2. Developmental concerns during emerging adulthood
Arnett (2004) coined the term emerging adulthood to capture the unique transitional period in human development that
occurs between late adolescence and young adulthood in cultural contexts where marriage and parenthood are delayed until the
late twenties or beyond. According to him, it is a “time of exploration and instability, a self-focused age, and an age of possibilities”
(p. 21). Two important developmental challenges faced by emerging adults include that of identity achievement and the
development of intimacy. Although the search for identity begins during adolescence (Erikson, 1959; Kroger, 2003), emerging
adults, particularly those in the western world, are still grappling with some aspects of their identities, such as their vocational/
career, religious, and ethnic identities (Cote, 2006). In addition, they seek to establish intimacy via interconnections with friends
and romantic partners, as well as relatives and family members. Non-romantic interconnections with others are the
developmental concern that is the focus of this paper. Friends are important to emerging adults, particularly for those not in a
romantic relationship (Kalmijn, 2003). Research suggests that self-disclosure is an important component of emerging adults’
feelings of intimacy in friendships and intimate behaviors with friends include “emotional support, trust and loyalty, sharing
activities, and offers of instrumental support” (Radmacher & Azmitia, 2006, p. 429). There is also evidence that support from such
intimate relationships may serve as a buffer against stress for college students (Cohen & Hoberman, 1983). Students appear to use
technology to obtain social support (LaRose, Eastin, & Gregg, 2001), and greater use of online communication tools such as email
and chat room/instant messaging is related to reduced depressive symptoms (Morgan & Cotten, 2003). Thus, the evidence to date
indicates that like adolescents, emerging adults may also use online communication tools in the service of important offline issues,
such as the need for interconnections with others and raises the possibility that their online and offline social networks overlap.
1.3. Emerging adults’ use of social networking sites for interconnection
Research on social networking sites is beginning to accumulate (boyd & Ellison, 2007b) and indicate that they may be used to
bridge online and offline social networks (see boyd & Ellison, 2007a for a review of prior work on this issue). Relevant to us is
research that has examined college students’ use of social networking sites to form and maintain interconnections with their
offline peers. For instance, in a survey of all incoming first year students at a major Midwestern university, Lampe, Ellison, and
Steinfield (2007) found that students most often used Facebook for social purposes — to stay in touch with their friends from high
school as well as to form interconnections with people they had met offline such as in their dormitories or in class. Similarly Ellison
et al. (2007) found that college students used Facebook to maintain or bolster existing offline connections rather than to form new
relationships. Such ties appear to have some positive benefits and greater Facebook use was associated with more perceived social
capital. Facebook use was related to all three kinds of perceived social capital — bridging social capital, which consists of the
resources that stem from one’s weaker ties, bonding social capital, which consists of the resources that stem from one’s more
intimate ties, and maintained social capital, which consists of the resources that stem from one’s prior ties.
Although these studies are beginning to show that emerging adults use social networking sites to connect with the people in
their offline worlds, questions remain as to how such use is integrated into their offline lives. For instance, what do emerging adults
do on social networking sites and what are their reasons for using these sites? What is the nature of their network of friends on
social networking sites and how do they decide whom to add or remove from their online network? What are the perceived effects
of these online interconnections on their relationships? Finally, it is important to note that the finding that emerging adults use
social networking sites to interconnect with people from their offline lives is based on self-reports from participants. To date no
study has asked users to list people from their face-to-face and social networking site networks and compared them. As of yet, we
do not know the actual relation between college students’ networks on social networking sites and their other online (e.g., instant
messaging) as well as offline networks — are the persons they interact with frequently on social networking sites the same as those
that they interact with frequently in face-to-face contexts as well as in another online context, instant messaging, or are they
different?
The purpose of the study was to determine what emerging adults do online, whom they interact with in cyberspace, and how
these online interactions relate to their offline relationships. Specifically, we expected to find that emerging adults, like many
adolescents, are daily users of the Internet and that their preferred uses would be social activities (e.g., participants would be more
likely to spend time emailing and on social networking sites than surfing the web or downloading music). In addition to expecting
high use of social networking sites, we anticipated that the most popular activities on these sites would be social in nature as well
(e.g., reading and posting comments would be more popular than checking out music links or joining new groups). Based on our
thesis that emerging adults’ online and offline worlds are connected, we predicted that there would be a high degree of overlap
between users’ top online and offline friends. Although we expected overlap between online and offline networks, we predicted
that more intensive users of the Internet would have less overlap between their online and offline networks. In summary, we
predicted that emerging adults would use social networking sites to promote social interaction and reinforce important offline
relationships, demonstrating that for them, technology is a tool for supporting interpersonal connections.
1.4. The present study
We addressed the above questions using a survey study of emerging adults in a large urban university. In order to determine
what emerging adults did online, how much time they spent on various online activities, especially on social networking sites, and
how their online and offline social networks related to one another, we used an offline paper-and-pencil survey as well as an online
423K. Subrahmanyam et al. / Journal of Applied Developmental Psychology 29 (2008) 420–433
survey to ask participants general questions about themselves, their offline and online activities, and their social networking site
use. In addition, they were asked more detailed questions regarding their social networking site use, such as their reasons for
having a profile, their frequent activities on social networking sites, how they decide to add or delete friends, and their perceptions
about the effects of their social networking site use on their relationships. Participants who did not use social networking sites
were asked whether they perceived any effects on themselves because they do not use these sites. Participants were also asked for
the names of the 10 people/friends that they interacted with the most in face-to-face-settings, in instant messaging, and on social
networking sites. Contingency tables (2 × 2 × 2) were then formed for each person to assess the degree of overlap between users’
online (instant messaging and social networking) and offline (face-to-face) networks.
A two-step procedure was adopted with the offline and online survey. Participants first completed the paper-and-pencil survey
in the laboratory, at which point they provided their email address. They were then sent an email with a link to the online survey,
and were asked to complete it while viewing their social networking profile and instant messaging buddy list. Methodologically,
such a two-step process has some advantages. Using an online survey enabled participants to answer detailed questions about
their social networking site/instant messaging use by checking their profiles online instead of relying on their memory or making
incorrect estimations, a problem encountered in previous survey studies of online activity (Subrahmanyam & Lin, 2007). The online
survey also asked participants specific questions about their time use that day — how much time they spent offline, online, and on
social networking sites as well as the activities that they had done on a social networking site that day. Using two different survey
formats allowed us to ask respondents what they usually do online and what they actually did on a particular day. This reduced
potential errors in participant’s recollection of online behaviors while offline and provided confirmation of certain aspects of
respondent’s identity such as gender and the fact that they were emerging adults in college. Thus, we were able to collect
information about participants’ online behavior while they were on the Internet, but without many of the uncertainties that often
accompany anonymous online surveys.
2. Method
2.1. Participants
A total of 131 participants were tested in the study. All participants were students in the Psychology participant pool at a large
urban university in Los Angeles, and they received course credit for their participation. To ensure that the sample was not skewed
in favor of social networking site users compared to non-users, the sign-up sheet described the study as investigating college
students’ use of the Internet and did not mention social networking sites or instant messaging. Twenty-one participants were
dropped from the study because they were not 18 to 29 years of age or did not provide their age. In our final sample of 110
participants (55 male and 55 female), the mean age of the participants was 21.5 (SD = 2.9) years. The sample was diverse and the
ethnic distribution of our participants reflected the diversity of Los Angeles (see Table 1 for details).
Of the 110 participants, five participants did not complete the online survey and an additional three did not fill out the
information about their networks accurately (e.g., they used screen names instead of actual names when answering questions
about their online friends); their data were retained for the analyses of the laboratory survey questions. Participants sometimes
failed to answer a question or did so incorrectly; therefore the actual number of responses included in a particular analysis is
indicated in parentheses. Although all of the 105 participants who completed the online survey provided the names of their face-
to-face friends, 46 did not use instant messaging, 23 did not use social networking sites, and a very small number made the mistake
Table 1
Demographic characteristics of the sample (N = 110)
Category n (% of sample)
Sex
Male 55 (50)
Female 55 (50)
Ethnicity
Latino/Hispanic (not white) 56 (51)
Asian/Asian-American 22 (20)
African-American 7 (6)
White 7 (6)
Other 15 (14)
Year in school
Freshman 20 (19)
Sophomore 25 (24)
Junior 34 (32)
Senior 27 (25)
Religion
Christian 72 (66)
Buddhist 7 (6)
Other 5 (4)
No religious affiliation 26 (24)
424 K. Subrahmanyam et al. / Journal of Applied Developmental Psychology 29 (2008) 420–433
of using screen names rather than real names when providing information about their online networks. As a result, only 81 listed
first and last names of online friends. As such, the analysis of network overlap was conducted on a subset of the participants (n = 81).
There were no significant differences between the participants included in the analysis of overlap from the rest of the sample on any
of the demographics, time spent online, or number of friends listed. The only differences identified, as would be expected, were that
participants in the online–offline comparison had a social networking site profile and an instant messaging account.
2.2. Measures
2.2.1. Laboratory survey
The research team developed a survey that presented questions about participants’ demographics and their use of social
networking sites, including questions about their typical activities on these sites (e.g., edit my profile, change my top “8”, write
comments on other people’s walls), motives for using them (e.g., stay in touch with friends, flirt, meet new people), and how they
decide who to add or delete from their social networking site networks (e.g., I will add any one who sends a friend request, I will
only add a person if they are a face-to-face friend). Most items asked respondents to check all answers that applied, some asked
them to rank order the frequency of activities, and a few provided open-ended responses such as reasons for blocking someone
from a profile or ways in which their social networking site use helped solve a conflict/problem. Participants who had social
networking site profiles were asked about their perceptions regarding the effects of their SNS use on their relationships; those
without profiles were asked how they felt about not having one and whether they visited social networking sites.
To map offline networks, participants were asked to list up to 10 people with whom they spend the most time. They were asked
to list the first and last names of these people as well as other information about them, such as their gender, age, and place where
they interacted with them the most (in school, out of school, or online). At the end of the survey, participants were informed that
they would receive a link via email for the online survey and were reminded to complete the survey before they went to bed.
2.2.2. Online survey
The online survey, hosted on Survey Monkey, was developed by the research team. The questions assessed participants’ offline
and online time use that day (e.g., How much time did you spend: downloading music, playing online games, emailing, etc.), their
social networking activities that day (e.g., What did you do when you visited MySpace/Facebook today: made a friend request,
updated profile, etc.), and the people they interact with the most via instant messaging and on social networking sites (e.g., How
well do you know this person?, Where do you spend the most time with this person?). As with the laboratory survey, participants
were asked to list the 10 people with whom they interact with most through instant messaging (e.g., AIM, MSN, Yahoo! Messenger)
and on social networking sites (e.g., MySpace, Facebook). Participants were also asked to provide additional information about
these online friends such as their first and last name, age, and relationship to them. Between the laboratory and online surveys,
participants provided the names of up to 30 people whom they interacted with most in online and offline contexts.
2.3. Procedure
When participants came to the laboratory, the informed consent document was first explained to them. After they signed the consent
document and provided their email address, they completed the laboratory survey (20–30 min). As they left the laboratory, they were
remindedthat they wouldreceive an email with a link totheonlinesurveyand wereasked tocomplete the15–20 minutesurveythat night.
2.4. Calculating the overlap between “friends”
Participants listed up to 10 people they interact with most in person, up to 10 people they interact with most on social
networking sites, and up to 10 people they interact most with on instant messaging. If a person named the same 10 people in all
three mediums (i.e., face-to-face, social networking sites, and instant messaging), then only 10 names were given. If there were no
overlaps across these three mediums then the participant would have provided up to 30 names. On average, people named a total
of 13 people with a range of 3–10 people per social medium (instant messaging, social networking site, and face-to-face).
Table 2
Contingency table created for each participant
Face-to-face friends (FTF) Not face-to-face friends (not FTF)
Do instant message
(IM)
Do not instant message
(no IM)
Do instant message
(IM)
Do not instant message
(no IM)
Use SNSs FTF that use SNS and IM
(use all three)
FTF that use SNS but
no IM
Total FTF that use
SNS
Not FTF that use SNS and IM Not FTF that use SNS but
no IM (SNS only)
Total not FTF
that
use SNS
Do not
use SNSs
FTF that do not use SNS
but IM
Only FTF (do not use
SNS and no IM)
Total FTF that do
not use SNS
Not FTF that do not use SNS
but do IM (IM only)
Not FTF that do not use
SNS nor IM (0)
Total not FTF that
do not use SNS
Total FTF that IM Total FTF that don’t IM Total FTF Total not FTF that IM Total not FTF that do not
use SNS
Total not FTF
Fig. 1. Pictorial representation of the overlap between each respondent’s instant messaging, social networking, and face-to-face friends.
Table 3
Participants’ time use (%) on each offline activity (n = 105) and online activity (n = 95)
Type of activity None 30 min or less 1 h 2–3 h 4 or more hours
Offline activities
Studying/schoolwork 21 19 19 28 13
Organized activity 75 7 7 9 2
Hanging out with friends 37 15 18 18 12
Talking on the phone 17 51 16 13 3
Watching television 21 27 22 27 3
Playing computer/video games 66 8 14 8 4
Job 65 3 0 7 25
Online activities
Email 8 74 15 3 0
Instant messaging 60 22 9 5 4
Blogging 73 23 3 1 0
Social networking sites 37 36 18 6 3
Gaming 89 4 4 1 2
Chat rooms 87 8 4 1 0
Web browsing 19 40 26 9 6
Downloading music 72 16 9 2 1
425K. Subrahmanyam et al. / Journal of Applied Developmental Psychology 29 (2008) 420–433
In order to determine the degree of overlap of friends that youth interact with most online and offline, we constructed 2 × 2 × 2
contingency tables for each respondent (see Table 2 for details). With these tables, we were able to calculate the percentage of overlap
across the three networks (e.g., the percentage of social networking friends who are also face-to-face friends, but not instant messaging
friends). The cells in each table provided an index of overlap per medium that could then be used for subsequent analyses. The Venn
diagram in Fig.1 is a pictorial representation of howeach cell of the 2 × 2 × 2 contingency table was calculated. For instance, the area “F” is
the overlap between friends on social networking sites and instant messaging that are not face-to-face friends, whereas the areas “G + F”
are thetotalnumberof friends that useinstantmessagingand aresocial network site friends (with “G” beingface-to-face friends as well).
3. Results
3.1. Offline and online time use
To get a snapshot of college students’ use of the Internet relative to their other activities, participants were asked on the online
survey about their offline and online time use that day. Table 3 shows the percentage of respondents who reported spending different
amounts of time on various offline (n = 105) and online activities (n = 95). As can be expected of college students, approximately 80% of
the sample reported spending some time studying/doing schoolwork, with 29% reporting that they studied between 2 to 3 h that day.
Participants reported spending little time engaging in other offline activities. For example, only 1/4 reported that they had spent any
time on organized activities such as sports and about 1/3 reported spending any time that day at a job. However, the majority reported
spending some time “hanging out” with friends and talking on the phone. While some played computer/video games (34%), many
more participants watched television (79%). Interestingly, 91% reported going online that day, more than those who reported studying
(n = 104). Visitingsocial networkingsites wasa popularonlineactivity, with 63% spendingsome time on these sites on theday that they
426 K. Subrahmanyam et al. / Journal of Applied Developmental Psychology 29 (2008) 420–433
completed thesurvey (n = 95). Large majorities of participants alsoreported spendingtime on email (92%)and web browsing(81%)that
day. In contrast, other online activities were engaged in by relatively fewer participants.
3.2. Use of social networking sites
To understand the role of social networking sites in college students’ lives, we analyzed basic trends in participants’ use of such
sites, their typical activities on them, and their reasons for using them.
3.2.1. Trends in the use of social networking sites
The majority of the participants in our sample reported having a profile on a social networking site (86 participants or 78% of
our sample) (See Table 4). Although slightly more males (82%) reported having profiles compared to females (75%), this was not a
reliable difference, χ2(1, N = 110) = 0.85, p N .05. Less common was the use of instant messaging programs such as AIM, and only
56% reported using them (n = 104); more males (65%) used instant messaging compared to females (46%), and this was a reliable
difference, χ2(1, N = 104) = 3.90, p = .05. There were no ethnic or religious group differences with regard to using instant
messaging, having a social networking site profile, and the kind of social networking site (e.g., MySpace, Facebook, or Xanga) used
and updated most frequently (all p’s N .05).
Eighty-eight percent of social networking site users reported that the profile that they updated the most often was on MySpace,
8% reported that it was on Facebook, 1% reported that it was on Xanga, YouTube, and other sites (n = 84). The number of profiles
reported by the social networking site users ranged from one through six (M = 1.69, SD = 1.05; Mdn = 1) with the majority (61%)
reporting having only one profile. Of the participants with a social networking site profile, most were daily users (57%; see Table 4 for
details). We found a comparable pattern of social networking site use in the time use data from the online survey. Among
participants who reported going online that day, prior to logging onto the online survey (n = 95), 63% reported going on to social
networking sites, with 36% reporting that they spent 30 min or less and 3% reporting that they spent four or more hours (see Table 3).
3.2.2. Activities and reasons for using social networking sites
On the online survey, participants were asked what they had done on a social networking site that day; on the laboratory survey,
they were asked to report the activities that they did most often on a social networking site. As can been seen from Fig. 2, the most
commonsocialnetworkingactivities that users didthatday included reading/respondingto notes/messages(77%),reading comments/
posts on their profile page/wall (75%), browsingfriends’pages/profiles/walls (66%), and writingcomments on friends’pages/postingon
other people’s walls/tagging photos (54%) (n = 35). Participants were also asked to rank their first, second, and third most frequent
activities on social networking sites (see Table 5). From Table 5, it is apparent that reading and responding to comments/posts on one’s
page/wall was an extremely popular activity among the participants in our sample and 60% chose it as their most frequent activity.
Browsing friends’ profiles/walls and sending/responding to messages were also repeatedly chosen as participants’ frequent activities.
Respondents’ motives for using social networking sites are shown in Fig. 3. Note that participants were asked to choose all the
reasons that applied to them. Fig. 3 suggests that participants reported using social networking sites primarily for social reasons that
involved people from their offline lives, such as keeping in touch with friends they do not see often (81%), because all their friends
had accounts (61%), keeping in touch with relatives and family (48%), and making plans with friends they see often (35%) (n = 86).
Social networking site users in our sample less frequently reported using social networking sites to look for new people (29%). For
college students, the more popular social networking activities involved interacting with other known users rather than looking for
new friends, new music, or finding groups to talk about specific issues.
Table 4
Participants’ use of social networking sites and instant messaging (n = 84)
Category N (% of sample)
Instant messaging 68 (62)
Social networking sites 86 (78)
Frequency of visits to social networking sites
Open all the time 2 (2)
Several times a day 22 (26)
Once or twice per day 25 (29)
Every 2–3 days 20 (23)
Once a week 6 (7)
Less than once a week 11 (13)
Number of social networking site profiles (M = 1.69; SD = 1.05)
One profile 51 (61)
Two profiles 14 (17)
Three profiles 14 (17)
Four or more profiles 4 (5)
Most updated profile
MySpace 74 (88)
Facebook 7 (8)
Other (e.g., Xanga, YouTube) 3 (4)
Table 5
Reported frequency of activities on social networking sites (% of participants)
Activity Most often (n = 80) Second most often (n = 78) Third most often (n = 76
Edit my profile and update my status 2 (3%) 5 (6%) 8 (11%)
Change my “Top 8” 0 0 1 (1%)
Change profile picture 3 (4%) 2 (3%) 7 (9%)
Read/respond to comments on my page/posts on my wall 43 (60%) 13 (17%) 3 (4%)
Write comments on other peoples’ page/wall 2 (3%) 16 (21%) 1 (15%)
Post/tag pictures 0 3 (4%) 1 (1%
Browse my friends’ profiles/walls/pages 10 (13%) 14 (18%) 12 (16%)
Wink, poke, give “e-props,” or kudos 0 1 (1%) 1 (15)
Create/visit groups to talk about specific topics 0 0 0
Listen to/find new music 1 (1%) 3 (4%) 8 (11%)
Look for the profiles of people I know or used to know 1 (1%) 6 (8%) 12 (16%)
Look for new friends, send friend requests, and add friends 0 2 (3%) 2 (3%)
Send/respond to messages/invites 11 (14%) 13 (17%) 10 (13%)
Fig. 2. Social networking site activities done that day (% participants).
427K. Subrahmanyam et al. / Journal of Applied Developmental Psychology 29 (2008) 420–433
3.3. Overlap between online and offline and networks
The2×2×2contingencytables(seeTable2forthelayout)foreachrespondentallowedustolook atthedegreeofoverlapbetweenclosest
friends on instant messaging, social networking sites, and face-to-face contexts. By calculating the percentages of overlap we were able to
control for the different numbers of people named across participants (e.g., one person named 5 instant messaging friends, 2 social
networking site friends, and 8 face-to-face friends while another listed 10 friends in each medium). In order to look at the overlap between
online and offline relationships, participants needed to provide first and last names for face-to-face friends and online friends (instant
messaging, social networking site or both). In total, 81 people listed first and last names of online (social networking site, instant messagingor
both) and offline friends. Of these, 70 provided names for instant messaging friends and 73 provided names for social networking site friends.
Fifty-four people listed names for both social networking site and instant messaging friends (i.e., provided names for all three contexts).
3.3.1. Overlap between offline and instant messaging networks
Of the 70 people who reported using instant messaging,11 had no overlap between their top instant messaging friends and face-to-
face friends. Only 12 people had 100% overlap as they used instant messaging exclusively with people who were also their top offline
friends. On average, half of the closest instant messaging friends’ names were also listed as closest face-to-face friends (M = 49%,SD= .35).
)
Fig. 3. Motives for using social networking sites (% participants).
428 K. Subrahmanyam et al. / Journal of Applied Developmental Psychology 29 (2008) 420–433
3.3.2. Overlap between offline and social networking site networks
While 81 people listed the first and last names of their online and offline friends, only 73 provided names for social networking
site friends. Of these 73, eight had no connection between their listed top social networking and face-to-face friends. Sixteen
people (22%) reported 100% overlap between their social networking friends and face-to-face friends. On average, 49% of people’s
top face-to-face friends were also their top social networking site friends (SD = .39).
3.3.3. Overlap between offline, instant messaging, and social networking site networks
Of the 54 people who reported using both instant messaging and social networking sites, slightly less than half (n = 24) reported no
overlap betweenthese two onlinemediums and their face-to-face friends and onlyonereported complete overlap betweenthese three
settings (i.e., exactly the same people were listed as face-to-face, instant messaging, and social networking site friends). However, five
people reported that all the people they instant messagewith were also their friends on social networkingsites (but not all were named
as face-to-face friends). In this sample, less than 1/3 of people’s friends on instant messaging and social networking sites overlapped.
3.3.4. Details about “friends”
For each person named by a respondent as a face-to-face, instant messaging or social networking site friend, participants
provided information about where they spent the most time with this person. In total, respondents (n = 81) could list up to 30
friends. Across all friends in all three mediums (face-to-face, instant messaging, and social networking site), respondents were
significantly more likely to spend time together out of school than in school or online, χ2 (2, N = 501) = 494.2, p b .0001. The sex of
the “friend” did not differ for males and females, χ2(2, N = 501) = 2.13, p = .12.
3.3.5. Factors related to overlap between online and offline networks
We also examined whethercharacteristics of social networking site users such as theirage, gender, and aspects of theironline behavior
were related to the extent of overlap between their various networks. With regard to age, of the 66 emerging adults aged 18–22 years, 44
(67%)usedinstantmessaging,45(68%)usedsocialnetworkingsites,and29(44%)usedboth instantmessagingandsocialnetworkingsites.
Of the 44 people aged 23–29 years, 26 (49%) used instant messaging, 28 (64%) used social networking sites and 19 (39%) used both instant
messaging and social networking sites. There were no significant differences in age and instant messaging or social networking site use or
use of both instant messaging and social networking sites (allp’s N .05). Therewere also no significant sex differences in online activities or
in the extent of network overlap, p = .12. The time spent online on the day of the survey was negatively correlated with overlap between
social networking and face-to-face friends, r = − .29, p b .05, suggesting that people who spent more time online that day had less of an
429K. Subrahmanyam et al. / Journal of Applied Developmental Psychology 29 (2008) 420–433
overlap between their top social networking site and face-to-face friends. We also found that online overlap (social networking sites and
instant messaging combined) correlated with using social networking sites to make plans with friends, (r = .30, p = .01), suggesting that
peoplewhoused SNSsas a toolto communicatewith theirofflinefriends alsohadgreateroverlap betweentheirsocialnetworkingsite and
face-to-face networks.
3.4. Friend networks on social networking sites
To describe the nature of emergingadults’ online networks onsocial networking sites, we asked social networkingsite users several
questions about the size of their networks, as well as how they added and deleted people on these networks. Participants’ online social
networking site networks were fairly large (M = 137, SD = 137, Mdn = 93,) and were reported to range in size from 0 (only one participant
reported having no one in their network) to 642 (n = 77). Although participants reported that they had met face-to-face many of the
people listed as an online social networking site friend (M = 101, SD = 113, Mdn = 69, Range = 600), they reported that they interacted
frequently with relatively fewer of their online social networking site friends (M = 25, SD = 38, Mdn = 16,Range = 300). Calculation of the
percentages for individual participants confirmed these overall trends — the mean percentage of online social networking site friends
participants had met face-to-face was 79% (SD = 27%, Mdn = 92%, Range = 5% to 100%) and the mean percentage of online social
networking site friends they frequently interacted with face-to-face was 29% (SD = 25%, Mdn = 21%, Range = 1% to 100%).
Further confirmation that emerging adults use social networking sites to connect with their offline friends comes from Fig. 4, which
shows that a majority of the social networking site users report that they only add people who they have met in person (73%); only a very
small minority (11%) report that they add anyone who sends a friend request (n = 85). Although the “Top friends” feature of social
networking sites (e.g., Top 8 in MySpace) is not very popular anymore, social networking site users’ response as to how theychoose whom
to add in this list is very revealing. A majority of the respondents (68%) reported that the people in their online “Top List” were also their
best friends offline; these “Top Lists” were not reciprocal in nature as only 15% reported that theironline “Top List” contained peoplewhose
“Top List” they were on. Despite the indications that emerging adults’ online and offline networksare linked, online networks appear to be
somewhat fluid as well; 64% of social networking site users reported that they had deleted a “friend” from their site and 39% had blocked
someonefrom theirprofile(n=84).Reasonsfordeletingorblockingrangedfrom losingcontact(“wedon’tKIT”[Keepintouch])towanting
privacy (“I don’t want any one but my close friends to see my profile”) to protecting one’s safety (“crazy stalker,” “My crazy ex-girlfriend”).
3.5. Perceived effects of social networking site use on relationships
Finally, participants were asked about their perceptions regarding the effects of their social networking site use on their
relationships. If they had a profile on a social networking site, they were asked whether their social networking site use had any
effect on their relationships with friends and family; they were also asked if their social networking site use had created any
trouble in their relationships or if it had helped to clear a misunderstanding. A majority of the social networking site users (73%)
reported that social networking site use had not made any difference to their relationships with friends, whereas 20% felt that it
Fig. 4. Persons who will be added as a friend on social networking profiles (%participants).
430 K. Subrahmanyam et al. / Journal of Applied Developmental Psychology 29 (2008) 420–433
had made them closer to their friends. Only a very small minority (2.5%) felt that it had negatively impacted their relationships with
their friends (n = 79). Although participants felt that their social networking site use had not affected their relationships or caused
trouble between them and their friends and family, a small minority (18 people out of 85; 21%) reported that something on their
profile had given them trouble. The most common sources of trouble were with romantic relationships (“Found out about cheating
& dates”) and changes to top 8 friends listed on the profile (“If I didn’t have that person on my top 8 it meant we were having a fight
or something”). Nine people (11%) reported that something on their social networking site profile helped fix a problem (n = 85).
These fixes tended to support claims of fidelity (“My boyfriend could read my comments that I’ve left for the guys and see that I’ve
done nothing to provoke obnoxious comments they’ve left me”) and provide a medium for addressing relationship problems
(“Make sure my friend wasn’t mad at me, where it would be harder to ask in person or by phone”).
Participants who did not have a profile on a social networking site were asked how they felt about not having one and if they
ever visited social networking sites, even if they did not have a profile. Although a majority (63%) of the respondents who did not
have a social networking site profile reported that not having a profile had no effect on them, 21% felt somewhat cut off from their
face-to-face friends and 13% felt pressure to get an account (n = 24). Only a very small minority (4%) felt very cut off from their face-
to-face friends because they did not have a social networking site profile. Not surprisingly, 56% of the people without profiles
reported visiting social networking sites, with a majority (11 persons or 52%) doing so less than once a week (n = 24).
4. Discussion
The results suggest that, as predicted, our participants’ use of social networking sites was integrated with both the concerns and
people from their offline lives. Emerging adults face the developmental task of establishing intimate relationships by forming and
maintaining interconnections with the people in their lives. The emerging adults in our sample seemed to be using social
networking sites to do just that — reports of their typical activities on social networking sites as well as their reasons for using these
sites suggest that they were using social networking sites to connect with others, in particular those in their offline lives. Similarly,
most users reported that they would only add people that they had met in person onto their network on social networking sites.
Analysis of the people that participants interacted with the most offline and on social networking sites confirmed that there was
some degree of overlap for most of them. Only a small minority had no overlap between these two groups of people. Despite these
links between their offline and online social networks, participants did not think that their use of social networking sites impacted
their relationships. Results of this study help to clarify the role of the Internet and social networking sites in the lives of emerging
adults.
4.1. Offline and online time use
To place our results in context, we start by briefly discussing our sample and our participants’ offline and online time use, in
particular their time on social networking sites. Our sample was ethnically very diverse — nearly 70% were Latino and Asian and
only 9% were White. Although much has been made of the digital divide with regard to Internet access (e.g., Lenhart & Horrigan,
2003) very few studies have taken a detailed look at urban minority youths’ use of technology, particularly with regard to social
networking sites. The present study fills this important gap in the literature. Although we only obtained a snapshot of participants’
time use, 91% reported going online the day that they took the survey, suggesting that the minority college students in our sample
were accessing the Internet at rates comparable to those reported in prior work (Jones, 2002). Moreover, judging by the percentage
of participants who engaged in various offline activities (see Table 3), the Internet was clearly important in their lives. One
difference from prior reports is that instant messaging was not that common an activity in our sample (Gemmill & Peterson, 2006;
Jones, 2002).
Our participants’ offline and online time use is also important from a developmental perspective. Offline, their most frequent
activities were talking on the phone, studying, watching television, and hanging out with friends. Online, their most frequent
activities were email, web browsing, and visiting social networking sites. Thus, the most frequent activities among college students
were studying, watching television, and interconnecting with others on the phone, via email, social networking sites, or in person.
Here we see that an important developmental concern of emerging adults, establishing and maintaining interconnections with
others, permeates through both their offline and online worlds.
4.2. Patterns of social networking site use
Although a large majority of our participants reported using social networking sites, the percentage of such use was slightly less
than that reported in other studies — 82% in our sample compared to 94% in Ellison et al.’s study (2007). One possible reason for
this difference may have been the age and demographics of our sample. Although Ellison et al. (2007) did not report the age range
of their participants, the mean age in their sample was 20.1 (SD = 1.64). Our participants were on average a bit older (M = 21.5 years,
SD = 2.9 years) and their ages were widely spread and ranged from 18 to 29 years. Most of the students at the university where we
conducted our study live at home and not on campus, and many work and have families of their own. All of these factors might
have contributed to the slightly reduced use of social networking sites that we found in our sample.
With regard to the particular social networking sites that were used, an overwhelming majority of our sample reported that
they used MySpace and only a small minority used Facebook. Again, this in contrast to the work by Ellison et al. (e.g., Ellison et al.,
2007; Lampe et al., 2007), who have reported strong use of Facebook by their participants. Note that a majority of our participants
431K. Subrahmanyam et al. / Journal of Applied Developmental Psychology 29 (2008) 420–433
were Latino and Asian, whereas the majority were White in Ellison and colleagues’ work. The use of MySpace in our sample is
consistent with Hargittai’s (2007) finding that even after controlling for factors such as parental education, context, and
experience, a user’s race and ethnicity were related to the specific social networking site that he/she uses. Specifically, she found
that compared to Whites, Latino students were significantly less likely to use Facebook and more likely to use MySpace. Hargittai
suggested that students from similar backgrounds might migrate to similar sites because people are looking for others in their
network to connect with on these sites. More research is necessary to understand whether the ethnic split in the use of particular
sites is reflective of a real difference in how individuals belonging to different groups use technology in general and social
networking sites in particular.
With regard to the actual use of social networking sites, most participants had only one profile and only a very small percentage
reported having multiple profiles; only a fourth of the sample reported visiting these sites several times each day and a very small
number reported having it open all the time. The daily snapshot confirmed these trends and only 10% of the sample reported
spending 2 or 3 h or more on social networking sites that day. It appears that the majority of our participants are moderate users of
social networking sites and only a very few reported heavy use. A previous study using a large sample of traditional-age college
students (n = 1300) found excessive use of the Internet in about 10% of the sample (Anderson, 2001) and the pattern of excessive
use in our sample appears to be in line with these trends.
4.3. Implications of social networking site use for development
Participants’ responses to questions about their frequent activities on social networking sites, what they did on social networking
sites that day, and their reasons for using social networking sites suggest that emerging adults use social networking sites to interconnect
with others. The college students in our sample used social networking sites as a means of staying in touch with their friends as well as
their family members and relatives; interestingly, they use them to keep in touch with friends they do not see that often as well as to
make plans with those they do see often. Furthermore, only a third of the participants reported that they had a social networking site
profile tomeetnewpeople andmakenewfriends, anda smallerpercentage reportedusingthem to flirt.Onlyanincrediblysmall number
of people reported that looking for new friends was something that they frequently did while on social networking sites.
Participants also reported that much of their time on social networking sites was spent reading comments, writing comments,
and responding to comments/messages. Browsing the pages/profiles of their friends was another favorite activity. Such browsing
of other people’s profile/walls helps users keep track of their friends, the events in their life, as well their friend’s interactions with
others. At the same time, being able to view interactions between members of one’s network can also create and help to fix
problems. A few of the participants reported trouble with their friends when they changed their list of Top 8 friends, whereas
several noted that the public nature of the comments helped to fix a problem (e.g., boyfriend read comments, girlfriend saw
relationship status). Among young people, such tracking of the members in one’s network is commonly called “stalking.”
Subrahmanyam’s college freshman daughter proudly announced that she is so good at finding people on Facebook that she was
recently able to find the photograph of someone who had a blocked profile. These informal observations suggest that “stalking”
may be emerging as an important means by which youth keep track of the many people in their networks as well as the
interactions that their network members have with others. Future research should examine how social networking sites are
making relationships and interactions that were previously private into more public and open ones and whether they might be
transforming them in the process. At the same time, it is worth noting that despite these apparent transformations, respondents
generally felt that social networking sites had not had any effect on their relationships.
Whereas it appears that emerging adults use social networking sites to connect with others, a core developmental issue in their
lives, it is important to consider that online phenomena are constantly changing and evolving and some applications have been
transient and relatively short-lived. Some of the trends in our study are worth noting in this regard. A very small minority of our
participants reported using social networking sites to share music and video files; yet when MySpace first began in Los Angeles, it
was an important means of bringing together music bands and people who were looking for new music (boyd & Ellison, 2007a,b).
Also relevant is that over half of the social networking site users in our study reported using them to fill up free time and not be
bored. A fifth of the users reported that their friends had made their profile and another fifth of non-users reported that not having
a profile led them to feel somewhat cut off. Not only are the uses of social networking sites constantly changing and evolving,
young people may be gravitating towards these sites because they are the popular new online tool that all of their peers are
flocking to. Thus, it is impossible to predict whether emerging adults will continue to use social networking sites for
interconnections and if they do, the particular manner in which they will do so.
4.4. Online and offline networks
Participants’ responses as to whom they add to their social networking site networks as well as analysis of their top online and
offline networks suggest that emerging adults use social networking sites to connect with people from their offline lives (see also
Steinfield, Ellison, & Lampe, 2008-this issue). However, the overlap between these mediums is not perfect suggesting that
emerging adults rank the level of importance of friends in different contexts in different ways. While more participants report
spending the most time with their friends outside of school (rather than online), only slightly more than half have any overlap
between their top instant messaging, social networking, and face-to-face friends and few (2.5%) have a perfect overlap between all
of these reported online and offline friends. It is also interesting that the degree of closeness varied by medium. Participants
reported that they do not look for strangers or add strangers to their social networking site network, but some of their closest
432 K. Subrahmanyam et al. / Journal of Applied Developmental Psychology 29 (2008) 420–433
online friends were different from their closest offline friends. Clearly, college students do not use social networking sites to meet
and form connections with strangers. Instead, they seem to use instant messaging and social networking sites to selectively
interact with different people from their offline world. In other words, they may be using social networking sites to strengthen
existing offline connections that may not be that strong within the context of their face-to-face lives. This is not uncommon in
other areas of people’s lives. For example, among older adults, one’s closest work friends are not necessarily the people one hangs
out with outside of work. Perhaps we are witnessing how emerging adults are developing the diversity of social spheres that adults
do, but through different avenues.
4.5. Connectedness of online and offline worlds
An important theoretical issue about online communication that motivated the current study is the extent of connectedness
that exists between young people’s offline and online lives. Our results indicate that college students use instant messaging and
social networking sites to interconnect with others, particularly those from their offline lives. They show that emerging adults’
offline and online worlds are connected and they use online communication for offline issues, and to connect with people in their
offline lives. Although young people’s offline and online worlds may be connected, they are certainly not mirror images of each
other. Whereas the top people listed in online mediums (instant messaging and social networking site) were not completely the
same as those listed as top face-to-face friends, youth did report spending the most time with their listed friends (from all three
mediums) in person, outside of school (i.e., not online). Thus, connectedness does not imply that young people’s online and offline
lives are identical. Instead it appears that when communicating online, young people may express offline concerns and interact
with people from their offline lives, but in a manner adapted to the particular affordances of the online context, such as its
opportunities (e.g., ability to create a public profile of oneself and have an extensive network of friends) and limitations (e.g., open
and visible interaction and lack of extensive face-to-face cues).
4.6. Limitations, conclusions, and future directions
As with any self-report survey, one concern is that participants’ responses may have been subject to biases, incorrect estimates,
faulty memories, and other similar problems. Since there was agreement betweenwhat respondents told us they typically did on social
networking sites and what they said theyactually did on a particular day, we think that for the most part participants were truthful and
consistent in responding to the survey questions. A second problem is that respondents were limited to listing 10 people — not all listed
10 and others may have had more than 10 that they interacted with often. Keep in mindalso that because participants were asked to list
only those whom they interacted with the most in each context, our estimates of network overlap are based on the top members of
networks in each context and not the overall networks. Although it may appear that our assessment of networks was not exhaustive
given that many participants had social networking site networks of over 100 friends, most of the respondents reported having regular
online contact with only a small percentage of these “friends.” Thus, asking about the top 10 rather than all their social networking site
friends may have actually helped us identify more important or intimate relationships. However, it also undoubtedly leads to an
overestimation of the degree of overlap between online and offline networks. A third limitation is that of attrition. On both surveys,
participants occasionally misunderstood a question (for e.g., when asked to rank their three favorite activities, they ranked all the
options, giving the same rank to several activities). Although having an offline and an online survey conferred several benefits, a small
number of participants failed to complete the online survey and those who did fill out both surveys made mistakes on occasion when
providing information about their friends in one or the other context (for e.g., one participant provided names for the face-to-face
context, but screen names for instantmessaging). Consequently, results for different questions are based on different sample sizes. Also
because we did not have complete network information for all participants, the sample size was reduced for analyses concerning
offline and online networks. Thus, we may not have had the statistical power to determine all of the factors that predicted the extent of
overlap between participants’ online and offline networks. However, our sample size was large enough to describe the degree of
overlap between online and offline networks, the central question of our study.
In conclusion, the results of our study show that emerging adults use social networking sites to connect with people from their
offline lives, such as their friends and families. Despite their use of these sites for interconnection, most did not perceive any effects on
their relationships. These trends were confirmed by the network analysis, which revealed that there was an overlap between
participants’ offline and online networks. This overlap wasnot perfect, suggesting thatemerging adults may beusingsocialnetworking
sites and instant messaging to selectively strengthen different connections within their offline networks. A question for future research
is whether emerging adults accrue different levels of intimacy and support depending on where a relationship is closest, in a face-to-
face or online context. Future work should also examine how variables such as users’ gender, social networking site use, offline
relationship strength, and perceived support might moderate the extent of overlap between their online and offline lives.
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- Online and offline social networks: Use of social networking sites by emerging adults
Introduction
Online communication in development
Connectedness between adolescents’ online and offline worlds
Connectedness between emerging adults’ online and offline worlds
Developmental concerns during emerging adulthood
Emerging adults’ use of social networking sites for interconnection
The present study
Method
Participants
Measures
Laboratory survey
Online survey
Procedure
Calculating the overlap between “friends”
Results
Offline and online time use
Use of social networking sites
Trends in the use of social networking sites
Activities and reasons for using social networking sites
Overlap between online and offline and networks
Overlap between offline and instant messaging networks
Overlap between offline and social networking site networks
Overlap between offline, instant messaging, and social networking site networks
Details about “friends”
Factors related to overlap between online and offline networks
Friend networks on social networking sites
Perceived effects of social networking site use on relationships
Discussion
Offline and online time use
Patterns of social networking site use
Implications of social networking site use for development
Online and offline networks
Connectedness of online and offline worlds
Limitations, conclusions, and future directions
References
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