Literature review

The topic is to discuss the evolution and current underdeveloped state of live streaming, particularly commercial live streaming. in the U.S

https://www.forbes.com/sites/jasongoldberg/2023/02/10/is-live-streamingcommerce-living-up-to-its-hype-in-the-us/?sh=75ed8de77a5a
https://onlinelibrary.wiley.com/doi/abs/10.1111/ijcs.12960
https://www.wsj.com/tech/will-livestreaming-be-tiktoks-amazon-killerafa9a0e6
Patterns of Communication in
Live Streaming
A comparison of China and the United States
SHUQIAN. ZHOU
MEIMEI. WANG
Master of Communication Thesis
Report nr. 2017:088
University of Gothenburg
Department of Applied Information Technology
Gothenburg, Sweden, May 2017
Patterns of communication in live streaming——A comparison of China and the United States
Acknowledgements
First of all, we would like to express our sincere gratitude to our supervisor, Prof. Jens
Allwood, for his weekly meetings during this half year and the constructive suggestions
to our thesis. We learned a lot from him, not only his profound knowledge in
communication, but also his rigorous academic attitude. We appreciate all of his efforts
in our thesis.
We would also like to thank our teachers of Master in Communication. They helped us
build our knowledge systems in communication from the very beginning and keep
enriching the systems within the two years. They also encouraged us to cooperate with
each other and present ourselves a lot. We are grateful for their help in our study.
Our sincere thanks also goes to our classmates, for their help and support for us in the
whole two years.
Finally, we must express our gratitude to our parents for providing us with unfailing
support and continuous encouragement throughout our two years of study. This thesis
would not have been possible without them.
Thank you all again.
Patterns of communication in live streaming——A comparison of China and the United States
Abstract
Live streaming as a social medium provides a multi-functional internet platform for its
users to have real-time interaction with others through broadcasting live streaming
videos by mobile devices and websites. It brings a new mode of communication. There
are previous studies related to its basic usage practices, user’s behavior and its
applications in specific fields, etc. However, this study is made from a communicative
perspective. It aims to describe and analyze the communication patterns in live
streaming. The study is a comparative study between China and the United States.
In order to study the communication patterns in live streaming, 106 live streaming
videos are observed (the total length of 2251 minutes). Combining qualitative analysis
with quantitative analysis, communication patterns in live streaming are analyzed based
on
relevant
communication
theories
including:
Interactive
Communication
Management, and Multimodal Communication. Cultural differences between China
and America are reflected during analyses of communication patterns in live streaming.
The findings demonstrate that there are common communication patterns in live
streaming in China and the United States. Common communication patterns are mostly
influenced or decided by traits of live streaming, the new social medium. Common
communication patterns in the two countries inference some general communication
patterns in live streaming. But, different communication patterns in live streaming in
China and the United States also exist. Indicating the cultural impact of the countries
on communication patterns in live streaming.
Key words: Live streaming, Communication patterns, China, the United States,
Culture.
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Patterns of communication in live streaming——A comparison of China and the United States
CONTENT
1. Introduction …………………………………………………………………………………………………. 6
1.1 What Is Live Streaming and What Are Communication Patterns? ……………… 6
1.2 Why Studying Communication Patterns in Live Streaming in Both China and
America? …………………………………………………………………………………………………. 7
1.3 Research Question and Purpose …………………………………………………………….. 8
1.4 The Framework of the Thesis ……………………………………………………………….. 8
2. Research Background …………………………………………………………………………………. 10
2.1 Development of Live Streaming ………………………………………………………….. 10
2.1.1 Development of Live Streaming in the United States ……………………………………… 10
2.1.2 Development of Live Streaming in China ………………………………………………………. 12
2.2. Functions and Features of Live Streaming …………………………………………… 13
2.3 Related Studies………………………………………………………………………………….. 16
3. Theoretical Framework ……………………………………………………………………………….. 21
3.1 Interactive Communication Management ……………………………………………… 21
3.1.1 Turn Management …………………………………………………………………………………….. 21
3.1.2 Sequence ………………………………………………………………………………………………….. 22
3.1.3 Feedback ………………………………………………………………………………………………….. 23
3.2 Multimodal Communication ……………………………………………………………….. 24
3.2.1 Dimensions of Production and Perception in Multimodal Communication………… 25
3.2.2 Body Movements ………………………………………………………………………………………. 26
4. Methodology ……………………………………………………………………………………………… 28
4.1 Study Design …………………………………………………………………………………….. 28
4.1.1 Observation and Coding Framework ……………………………………………………………. 28
4.1.2 Types of Live Streaming to Be Observed……………………………………………………….. 30
4.2 Data Analysis ……………………………………………………………………………………. 31
4.3 Ethical Consideration …………………………………………………………………………. 32
5. Results and Analyses…………………………………………………………………………………… 33
5.1 Overview of the Observation Data ………………………………………………………. 33
5.1.1 Demographics of Broadcasters……………………………………………………………………. 33
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Patterns of communication in live streaming——A comparison of China and the United States
5.1.2 Place Broadcasting ……………………………………………………………………………………. 34
5.1.3 Number of Viewers ……………………………………………………………………………………. 35
5.1.4 Interactivity in China and the USA ……………………………………………………………….. 37
5.2 Interactive Communication Management ……………………………………………… 38
5.2.1 Turn Management …………………………………………………………………………………….. 39
5.2.2 Feedback ………………………………………………………………………………………………….. 41
5.2.3 Sequence ………………………………………………………………………………………………….. 49
5.3 Multimodal Communication in Live Streaming …………………………………….. 50
5.3.1 Specific Multimodal Communication in Live Streaming ………………………………….. 50
5.3.2 Body Movements in Live Streaming …………………………………………………………….. 52
5.3.3 Flexibility of Multimodal Communication in Live Streaming ……………………………. 58
5.3.4 Multimodality in Different Contents of Live Streaming …………………………………… 59
6. Discussion …………………………………………………………………………………………………. 61
6.1 Delayed Answers from Broadcasters ……………………………………………………. 61
6.2 Questions Chosen by Broadcasters ………………………………………………………. 63
6.4 Lack of Understanding ……………………………………………………………………….. 65
6.5 Embarrassment Hiding……………………………………………………………………….. 66
7. Conclusion ………………………………………………………………………………………………… 68
7.1 Patterns of Communication in Live Streaming ………………………………………. 68
7.2 Differences between Chinese and American Live Streaming …………………… 69
7.3 Limitations and Future Studies ……………………………………………………………. 71
References …………………………………………………………………………………………………….. 72
Appendices ……………………………………………………………………………………………………. 77
Appendix 1 Observation Schema………………………………………………………………. 77
Appendix 2 Cluster Membership in USA …………………………………………………… 79
Appendix 3 Cluster Membership in China …………………………………………………. 81
Appendix 4 Division of Work …………………………………………………………………… 83
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Patterns of communication in live streaming——A comparison of China and the United States
1. Introduction
1.1 What Is Live Streaming and What Are Communication Patterns?
In previous studies, the new social medium of live streaming is not given a complete
and accurate definition. Powell (2015) says that live streaming essentially allows you
to capture and stream, or watch, live video on your mobile device. Hamilton et al. (2014)
claim that live streaming enables public broadcast of live audio and video streams
alongside a shared chat channel. Pires et al. (2015) mentioned that live video streaming
systems are services that allow anybody to broadcast a video stream over the Internet.
Juhlin et al. (2010) state that live streaming makes it possible to capture live video on a
mobile phone and broadcast it in real time to a web page. Hamilton et al. (2016) claim
that live streaming has come to refer to live, streaming, video as well as a set of
communication media that enable viewers to interact with each other and the streamer.
From these descriptions, there are three factors that need to be considered when defining
live streaming, live videos and audios, through mobile devices or internet, interacting
or sharing with others. Therefore, based on the definition of Tang et al. (2016), live
streaming enables immediate live broadcasting of video and audio from a smartphone,
to whomever wants to tune in. We define live streaming as: a social medium that
provides a multi-function internet platform for its users to have the real-time interaction
with others through broadcasting live streaming videos by mobile devices and websites.
Communication patterns refer to specific features of communication that are typical of
a certain community or activity, such as typical sequence of events, feedback, turn
taking, or spatial arrangements, topics, nonverbal behavior etc. Therefore, the number
of such aspects and traits is large and what is at stake is, therefore, to focus on aspects
and traits which have turned out to be interesting in a given community or activity
(Allwood, 1999). According to Allwood (1999), the concept of “patterns of
communication” is fairly general and does not imply very much more than repeated
traits of, or aspects of the communication of the members of a certain social or cultural
group. He has focused on cultural reasons or influences for communication features
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Patterns of communication in live streaming——A comparison of China and the United States
when studying communication patterns. Other studies have analyzed communication
patterns from the perspective of management and had claimed communication patterns
are structures in which communication flows in an organization (Mishra, 2017). This
study also focused on the communication links in work teams according to
organizational structures. It is clear that different perspectives focus on different aspects
when talking about communication patterns.
This study analyzed communication patterns in live streaming in both China and
America, it focuses on features of communication and basic structure of communication
patterns in live streaming. Meanwhile, cultural factors are also considered in the
analysis, particularly when they are the main reasons for differences between Chinese
and American live streaming communication.
1.2 Why Studying Communication Patterns in Live Streaming in Both China and
America?
Live streaming not only brings new opportunities for the development of social media,
more significantly, it creates new communication modes for social media users. People
are not satisfied to post personal status on Facebook or Twitter anymore, they broadcast
their lives, e.g. concerts they are enjoying, activities they are participating in, travels
they are experiencing, etc. Through live streaming, they share lives and interact with
whomever wants to tune in directly and in real time. Moreover, communication is the
basis of live streaming. Broadcasters can communicate with viewers through videos,
audios or graphics, while the audience can only use text-based comments or tap hearts
up to communicate with broadcasters. This interactivity is important in live streaming.
As above, this new mode of communication has great potential as data for research.
However, through our analyses of previous works, they paid more attention on, for
instance, live streaming usage practices; broadcasters’ behaviors; audience psychology,
etc., but not on patterns of communication. Thus, we study live streaming from a
communicative perspective. This study aims to describe and analyze communication
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Patterns of communication in live streaming——A comparison of China and the United States
patterns in live streaming.
In general, interactivity in live streaming, and the communication mode brought by this
new medium, as well as the analyses of previous studies provide us great motivation to
study patterns of communication in live streaming.
In addition, the huge development potential of live streaming attracts a lot of attention
in both the USA and China. From 2015, in the USA, 4 live streaming platforms emerged
one after another. They belonged to Twitter, Facebook, and Google, which are giants of
American social networking or internet companies in America. In China, according to
Statistical Report on Internet Development in China (2017), there are more than 200
platforms till 2017. And by the end of December 2016, online broadcast users reached
344 million, accounting for 47.1% of the total Internet users. The very rapid
development of live streaming in China and America probably make them the most
advanced countries when studying live streaming.
1.3 Research Question and Purpose
This study tries to answers the question: What are communication patterns in live
streaming in China and the United States?
According to this research questions, purposes of this paper include i) describe and
analyze basic features of communication in live streaming, ii) construct the basic
structure of communication in live streaming, iii) demonstrate similarities and
differences between live streaming communication and face-to-face communication in
relevant analyses, (iv) compare specific traits of communication in live streaming in
China and America from a cultural perspective. This thesis aims to show a clear and
complete picture of communication patterns in live streaming.
1.4 The Framework of the Thesis
This thesis consists of seven sections. The first section, introduction, mainly introduces
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Patterns of communication in live streaming——A comparison of China and the United States
research question and purposes of the thesis. The second section, research background,
includes developments of live streaming in the United States and China, basic functions
and features of live streaming, as well as prior studies in this field. The third section
shows the theoretical framework of used in the thesis. After that the method used in this
study will be introduced. Then, in the results and analyses section, results from the
empirical data are described, analyzed and compared according to the theoretical
framework. The next section discusses special aspects focused on during observations.
The final section concludes the whole thesis, displaying the main findings in our study.
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Patterns of communication in live streaming——A comparison of China and the United States
2. Research Background
In this chapter, we introduce live streaming and describe its development, main
functions and features, as well previous related studies. The purpose is giving a clear,
general understanding of this new social medium.
2.1 Development of Live Streaming
The emergence of live streaming as a popular medium in recent years provides a new
platform for socio-technical interaction in the world (Tang et al., 2017). The popularity
of live streaming platforms, Periscope and Twitch, Facebook etc. , have attracted a lot
of users, media attention, and capital injection. However, Rome was not built in a day,
live streaming has its course of development.
2.1.1 Development of Live Streaming in the United States
In the United States, the earlier live streaming platforms can be traced back to Ustream
and Justin.tv. Both of these two platforms were built in 2007. These two social
platforms were seen as the founders of live streaming. At the time, their service worked
off webcams hooked to computers for the first time (McDermott, 2015). They allowed
users to broadcast, and watch, live video streams online.
Ustream (acquired by IBM) was famous for its real-time broadcast of political events,
while Justin.tv made the huge success on its gaming channel, which became a separate
website called Twitch.tv in 2011. Till 2014 (Twitch was acquired by Amazon with $970
million), Twitch has become one of the largest live streaming platform in the world and
it held the leading position in gaming live streaming market. According to Hamilton et
al. (2014), Twitch has over 34 million unique monthly viewers and tens of thousands
of streamers.
The success of Twitch is a turning point for the development of live streaming. Huge
capital investment by big companies, IBM and Amzon, not only opened new market
for live streaming, but also attracted more attention from the public. In 2013, the
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Patterns of communication in live streaming——A comparison of China and the United States
implementation of 4G LTE (Long-Term Evolution) mobile networks, a high-speed
protocol that transmits data 10 times faster than 3G, made it much easier to send and
receive video from cellphones (McDermott, 2015). 4G service broke the technological
limitations for live streaming. Therefore, with large capital injection, 4G technology
and the maturity of social platform (Twitter, Facebook, etc.), live streaming ushered in
the golden age of its development.
In February, 2015, San Francisco entrepreneur Ben Rubin announced the launch of his
live streaming’ video application, Meerkat (Edelman, 2016). This application allows
users to shoot video footage on their smartphones and simultaneously make that footage
appear in real time on the internet, and allows watchers to comment live.
Just 2 weeks later, Twitter cut off Meerkat’s (shut down in October, 2016) integration
with its feed and announced its similar online application, Periscope (McDermott,
2015). Periscope allow users to follow broadcasters and comment on or “heart” the
videos. Unlike Meerkat, Periscope broadcasts persist on the app for 24 hours after a
filming (McDermott, 2015). Meerkat and Periscope instantly became rivals and have
been developing features to set themselves apart from each other.
In August 2015, Facebook introduced its app Facebook Live for only celebrities with
the verified Pages. Then on April 6th, 2016, Zuckerberg announced they were
launching Facebook Live for all users. Anyone with a phone now has the power to
broadcast to anyone in the world when they using Facebook. Besides personal users,
there are many news media, such as BBC, starting to broadcast live news by using
Facebook Live. After that, on August 26th, 2015, YouTube launched its first live
streaming channel, YouTube Gaming—a video game oriented platform. After that, they
opened more live streaming channels such as sports, technology, animal etc.
From the above, through the development of representative live streaming platforms in
the United States, it is clear to see that, in the year of 2015, there was the boom of live
streaming after the success of Twitch. This boom is inseparable from progress of
technology, market investment, the participation of social platforms. The continuous
emergence and growth of new platforms showed the flourishing development of live
streaming.
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Patterns of communication in live streaming——A comparison of China and the United States
2.1.2 Development of Live Streaming in China
In China, based on the information we collected from the official websites of live
streaming platforms and national Statistical Report on Internet Development (2017),
the development of live streaming can be divided into three phases.
Before 2013, 9158, YY Live (changed name to Huya Live in January, 2014) etc. were
the main platforms at the time. Early live streaming platforms mainly focused on live
show. They provided internet platforms for individual broadcasters to show personal
talent (like sing, dance etc.) or chat with viewers through broadcasting on live streaming
platforms. Broadcasters could get salaries from platforms. Early live streaming
platforms built this underlying business model of live streaming in China.
From 2014 to 2015, gaming live streaming had a huge development in China because
of the emergence of two big live streaming platforms, Douyu and Panda.tv.
In January, 2014, Douyu and Zhanqi were launched at same month. Both of them
focused on gaming video. However, Douyu defeated Zhanqi after launched and became
the leader of gaming live streaming market in China. Douyu’s official website showed
that it has more than 70% market of gaming live streaming in China. In 2016, its
popularity and profitability also won $100 million investment from Tencent (one of
Chinese largest Internet companies).
After that, in October, 2015, Panda.tv was launched by Sicong Wang, son of the richest
man in China. Panda.tv also mainly focus on gaming video. It developed very quickly
with the support of abundant funding. Till now, it has become the biggest rival to Douyu
in gaming live streaming market.
Both Douyu and Panda.tv increase the competitiveness of gaming live streaming in
Chinese live streaming market. Moreover, their success also brought the prospect of a
better development of live streaming in China.
After 2016, Inke and Yizhibo showed new development direction of live streaming in
China. Inke was launched in May of 2015, as a platform of live streaming, not like
Douyu or Panda.tv, which focus on gaming video, Inke included so many different
contents, such as live show, sports, music, travel etc. It is quite popular as the platform
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Patterns of communication in live streaming——A comparison of China and the United States
of live streaming among young people. Yizhibo was launched in March, 2016 by Sina
(one of Chinese largest Internet companies). It can be used with Weibo (microblog).
Yizhibo developed very fast and got much investments from Sina. It is similar to Inke,
users can broadcast many different things in their life, no matter their home dinner or
football games they watched.
The popularity of Inke and Yizhibo shows that live streaming in China is changing from
specialization to popularization. More and more ordinary people use live streaming to
broadcast their daily life. Live streaming does not only focus on live shows or gaming
videos anymore. According to Statistical Report on Internet Development in China
(2017), there are more than 200 live streaming platforms in China till 2017. Most of the
platforms are trying to expand the content of live streaming, especially live streaming
about their daily life and live streaming programs in order to attract more types of users.
To contrast with live streaming in the United States, Chinese live streaming has its
unique business model. On most of American platforms (except Twitch), the
broadcasters do not have incomes from live streaming, the audience watch for free.
However, in China, broadcasters on most platforms have incomes. Their incomes are
depended on the number of the audience and the virtual gifts they get from live
streaming. The audience buy virtual gifts by real money on the platforms. After
broadcasting, platforms and broadcasters distribute money in certain proportion. In this
way, live streaming shows strong profitability in China.
2.2. Functions and Features of Live Streaming
Live streaming provides a multi-function Internet broadcast platform for broadcasters
to have real-time interaction with others through immediate live broadcasting of video
and audio from a computer or mobile smartphone. Live streaming combines highfidelity graphics and video with low-fidelity text-based communication channels to
create a unique social medium (Hamilton et al. 2014).
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Patterns of communication in live streaming——A comparison of China and the United States
The typical live streaming experience consists of a broadcaster broadcasting a video
stream accompanied by a dedicated chat channel (Hamilton et al. 2016). Through live
streaming’s user interface, both broadcasters and audience can see graphics and videos
from broadcasters, as well as the comments from all audiences. However, broadcasters
cannot use text-based functions to communicate with the audience, in contrast, the
audience can only use text-based functions to give comments or feedback to
broadcasters.
The essential functions of live streaming are allowing users to broadcast or watch real
time live video on relevant platforms. Streaming video in real time means people all
around the world can watch whenever/whatever you are broadcasting through relevant
platforms (Powell, 2015). Through this function, live streaming provides a new way for
its users to share experiences as they happen with no editing or uploading. Real time
broadcasting as one of the significant factors of live streaming appeals to the human
desire to live out new experiences vicariously through someone else, whether the
streams are by a stay-at-home dad cooking dinner or a celebrity taking viewers through
a red carpet event, users can broadcast themselves (Brouwer, 2015). Sharing one’s own
experiences or participating in some things vicariously through others’ experiences
show the most unique and significant value of live streaming.
Some functions and features of live streaming can be described by introducing two
representative live streaming platforms, Periscope (from the United States) and Yizhibo
(from China). As two professional and mature live streaming platforms, they have some
similar functions.
After users choosing to create new accounts or login by their Twitter/Weibo accounts,
they can shoot or watch live streaming videos on the platforms. Both Periscope and
Yizhibo allow users to follow broadcasters. When seeing the live streaming videos,
viewers can comment on or “heart” the videos. Figure 1 and 2 respectively show two
screenshots of viewing a live stream in both Periscope and Yizhibo apps at the time of
the observation of this study (April, 2017).
Periscope show the number of viewers in lower right corner as part of the live stream
for all to see (Tang et al, 2016). While Yizhibo only show who are watching this video
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Patterns of communication in live streaming——A comparison of China and the United States
at the same on the top of the image. Yizhibo shows broadcasters’ information at the
upper right corner, however, Periscope does not shows broadcasters’ information.
Periscope broadcasts persist on the app for 24 hours after a filming, while Yizhibo can
save the videos more than 24 hours. Both of Periscope and Yizhibo users can set their
app to notify them if those whom they follow are broadcasting. In addition, both
applications eat cellphone power and bandwidth, so it is recommended that broadcasts
be made over a WiFi connection.
Figure. 1 Viewing a live stream in Periscope
Figure. 2 Viewing a live stream in Yizhibo
From the above, we see that the main functions of live streaming are allowing users to
broadcast or watch real time live video. These functions enable remote viewers to
engage and participate in shared live experiences (Hamilton et al. 2016). Users can also
follow other broadcasters, set notifications, give text-based comments and tap hearts
when watching live streaming videos. During live streaming, broadcasters and viewers
communicate with each other by different modalities. And their interactions are always
real-time and simultaneous.
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Patterns of communication in live streaming——A comparison of China and the United States
2.3 Related Studies
The rapid development of live streaming has drawn the attention of some scholars. A
number of studies on live streaming have been conducted in different academic fields.
McDermott (2015) quoted above and Cui (2016) provided the general introduction of
live streaming respectively in the United States and China.
McDermott (2015) introduced important nodes in the development living streaming in
the United States: from YouTube, Ustream, to Meerkat, Periscope, and Facebook live.
She focused on analyzing the history of development of Meerkat, Periscope, and
Facebook live. She also compared advantages and shortcomings of Meerkat and
Periscope by analyzing features of their interfaces. Cui (2016) analyzed the categories
of living streaming in China. She summarized four live streaming categories: live
streaming focusing on publishers’ performance, live streaming focusing on audience
reaction, live streaming focusing on the content, and live streaming focusing on
constructing specific scene. She also claimed that PUGC (professional user-generated
content) will replace UGC (User-Generated Content) and PGC (Professionallygenerated Content) and becoming the main trend in the future live streaming in China.
Tang et al. (2016), Siekkinen et al. (2016), Lim et al.(2012), Juhlin et al. (2010), Weisz
et al. (2007) studied the usage practices/patterns of live streaming or mobile live video
service.
Tang et al. (2016) made a comparative study about live streaming by comparing
Meerkat and Periscope apps for live streaming mobile devices. They described the
contents, settings, and other characteristics of live streaming. They found that most of
streamers were motivated to broadcast in order to develop their personal brands.
Moreover, they studied a range of streamers’ responses to their viewers’ comments and
found that the highest percentage of streamers who actively or sometimes responded
occurred in chats, conversely, streaming a professional or amateur event had lower
percentages of responsive streamers.
Siekkinen et al. (2016) explored the anatomy of a mobile live streaming service by
doing the case study of Periscope. They studied live streaming service to understand its
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Patterns of communication in live streaming——A comparison of China and the United States
usage patterns and technical characteristics of the service (e.g. delay and bandwidth)
and also performed the adaptation strategies of using Periscope. Lim et al. (2012)
studied usage practice by constructing a social media-enhanced real-time streaming
video service prototype and conducted a field experiment with actual social media users.
Their research results indicate that: inhabited space (the degree of being situated in
context and in a meaningful place) and isomorph effects (the degree of preserving the
structure of a user’s actions) reduce psychological distance between users, and this, in
turn, enhances co-experience.
Juhlin et al. (2010) were interested in mobile live video and user-generated content.
They provided a qualitative content analysis of four such services (bambuser.com,
qik.com, flixwagon.com, and kyte.com.). Their analysis revealed how broadcasters
utilize the different affordances (text, photography, audio, video files) of this new
medium. Weisz et al. (2007) studied people’s experience of watching videos online,
while simultaneously chatting with others using a text chat feature. Through
experiments, they found that new peer-to-peer video streaming technologies
fundamentally change the passive way we experience media, people actively engage
with each other as engaging with the video, but active engagement comes at a cost.
Zhang and Liu (2015), Pires et al. (2015), Shamma et al. (2009), Kaytoue et al. (2012)
studied the interaction between publishers and viewers in live streaming from the
different perspective. Specially, Shamma et al. (2009), Kaytoue et al. (2012) explored
the interaction between publishers and viewers when building virtual communities in
live streaming.
Zhang and Liu (2015) focused on the multi-sourced live streaming broadcasters’ and
viewers’ interactive experience from the technological perspective. They made a
measurement study by taking Twitch as a representative. The results revealed that
current delay strategy on the viewer’s side substantially impacts the viewers’ interactive
experience. On the broadcaster’s side, the dynamic uploading capacity is a critical
challenge. Pires et al. (2015) focused on the User-Generated live video streaming
systems. They presented a dataset for three months of traces of both Twitch and
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Patterns of communication in live streaming——A comparison of China and the United States
YouTube. They found that both systems generate a significant traffic with frequent
peaks at more than 1 Tbps.
Shamma et al. (2009) addressed the ways in which DJs have adopted one webcasting
technology, Yahoo Live. They found that three overlapping communities that are
important to the DJs, with whom they want to maintain reliable and consistent
connection. They also claimed that during the asynchronous interaction, small cues,
feedback, music, chat facilities and the potential for eye-gaze with audience members
offer a connection between the DJ and their audiences. Kaytoue et al. (2012) studied
Electronic-sport (E-Sport) by analyzing Twitch.tv. In their paper, they found that a new
Web community for e-sport fans watching live streaming was emerging. Their results
also show that tournaments and releases translate into clear growths of the game
audience.
Hamilton et al. (2014, 2016) did studies about how live streaming fosters participation
and builds community. Hamilton et al. (2014) presented an ethnographic investigation
of the live streaming of video games on Twitch. They found that Twitch streams act as
virtual third places, in which informal communities emerge, socialize, and participate.
The assemblage of hot (video) and cool (text) media enables live streaming to provide
an open place for people to go socialize, play, and participate in something larger than
themselves. Hamilton et al. (2016) studied how to support communication and
participation in multi-stream experiences, they presented the design and evaluation of
Rivulet, and found that viewers use all modalities (text chat, Push-To-Talk, and hearts)
to engage with the streamers. They also found that multi-stream experiences led to
interesting cross-stream interactions. Viewers were able to easily find and participate
in streams that addressed their interests and desire for engagement.
House (2016) and Thorburn’s (2013) studied live streaming from a political perspective.
Thorburn’s (2013) article seeks to critically examine the practical application of live
streaming video at use in contemporary resistance movements. She claimed that
political actors and digital technologies can form unique assemblages, which can both
operate as mechanisms of power as surveillance technologies for police forces and open
up nodes of counter-power, disrupting state surveillance. House (2016) claimed that
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Patterns of communication in live streaming——A comparison of China and the United States
live streaming is a dynamic assemblage of technologies, practices, and participants that
destabilizes the boundaries of who is a participant and even what, where, and when is
an event. She found that the embodied, immediate, and intimate nature of livestreaming could promote mutual understanding and interaction among protesters,
police, and distant viewers.
Ding et al. (2011) explored the behavior of broadcasters in live streaming. Yuan et al.
(2016), Li (2015), Jia (2016) studied the audience psychology in live streaming in China.
Ding et al. (2011) studied YouTube uploaders and conducted extensive measurement
and analysis of them. They found that: among these uploaders, the most active 20%
uploaders contribute 72.5% of the videos; there are more than three times male
uploaders than female uploaders. Furthermore, they found that much of the content in
YouTube is not user generated. Many YouTube uploaders are user copied rather than
user generated. Yuan et al. (2016) explored the psychological phenomenon behind live
streaming. He claimed that live streaming’s turning from the public space to private
sector also leads viewers’ complex psychological logic. According to Foucault’s theory
of the panoramic view and Lacan’s gaze theory, they claimed that viewer’s watching
behavior reveal a kind of self-image construction and self-identity reshaping. It also
reflected people’s needs of peep and sexual drive. Jia (2016) studied audience
psychology by using Goffman’s Dramaturgical model. He also claimed that live
streaming puts back stage in front and it satisfied viewers’ need of peep.
Brouwer (2015) and Birkner (2016) studied live streaming from a business perspective.
Brouwer (2015) explored how broadcasters could use live streaming for business
purposes while delivering high-quality broadcast experiences to their audiences and
customers. She claimed that accessibility makes live streaming much more powerful.
Birkner (2016) emphasized that the significance of Periscope to organizations is -allowing organizations to humanize their brand. Periscope makes it simple for brands
to connect with their consumers on a personal level.
From the analysis above, previous studies of live streaming are mainly about usage
practices; usage patterns; interaction between broadcasters and audiences; building
virtual communities; fostering participation; roles of political tools; broadcasters’
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Patterns of communication in live streaming——A comparison of China and the United States
behaviors; audience psychology and business benefits. Comparative study, case study
and measurement study are used in this filed. Twitch, Meerkat, Periscope, YouTube
live and Facebook live are usually taken as representatives. In general, prior works
focusing on American live streaming platforms give us an early glimpse at a rapidly
evolving social communication technology. The studies in China, however, focus more
on psychological reasons why the audience watch live streaming videos. All of these
show us important studies about live streaming in different fields.
According to the research background, it is clear that studies on live streaming focus
on very limited fields. There is no previous study focusing on communication patterns
in live streaming.
20
Patterns of communication in live streaming——A comparison of China and the United States
3. Theoretical Framework
In order to analyze communication patterns in live streaming, we base our analysis on
a theory framework. It includes two parts: interactive communication management and
multimodal communication. These theories are described one after another.
3.1 Interactive Communication Management
Simultaneous communication in live streaming involves lots of interlocutors. To make
this multilateral communication go successfully, interactivity in live streaming is very
important. When analyzing interactivity in live streaming, a theory of interactive
communication management is used in this study. Interactive communication
management (ICM) refers to the features of communication supporting interaction, e.g.
mechanisms for management of turns, feedback, sequencing, rhythm and spatial
coordination (Allwood, 2008b). Turn management, feedback, and sequence of ICM are
used in this study.
3.1.1 Turn Management
A turn is defined as a speaker’s right to the floor (Allwood, 1999a). Turn management
regulates the interaction flow and minimizes overlapping speech and pauses (Allwood
et al., 2007). When we have two-way interactive communication, turn management as
mechanisms and processes are essential (Allwood, 2010).
Three general features of turn management are turn gain, turn end and turn hold
(Allwood et al., 2007). Turn gain can be divided into turn taking and turn accepting.
Turn taking means the speaker takes a turn that wasn’t offered, possibly by interrupting,
while turn accepting means the speaker accepts a turn that is being offered. Similarly,
turn end also can be divided into two types. Turn yielding means the speaker releases
the turn under pressure, while turn offer means the speaker offers the turn to the
interlocutor, or a turn complete if the speaker signals completion of the turn and end of
the dialogue at the same time (Allwood et al., 2007).
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Patterns of communication in live streaming——A comparison of China and the United States
3.1.2 Sequence
Activities can be subdivided into different sub-activities. If we take one live stream as
an activity, it should consist of several sub-activities. Each sub-activity has its sequence
from start to end. A common sequence is the following (Allwood, 1999a).
(i) Initiation (opening, entering an activity, a sub-activity or a topic)
(ii) Maintenance (maintaining a sub-activity or topic)
(iii) Changing (changing a sub-activity or topic)
(iv) Ending (closing an activity, a sub-activity or a topic)
When it comes to specific patterns of communication, there will be typical sequences.
The expression “typical sequences of events” is intended to refer to the fact that what
happens in a conversation often happens in a certain sequence (Allwood, 1999b).
Different cultures, different activities have their own sequence of communication,
varying in initial sequences, medial sequences, and final sequences. Open sequence,
continue sequence and close sequence are used to analyze different stages of a
meaningful sequence (Allwood et al., 2007).
Contributions often occur in fairly set sequences, such sequences extend from
“exchange types” (Allwood et al., 2012). In particular activities, preferred types of
responses are used to reply certain comments. For example, in live streaming,
broadcasters usually express gratitude verbally and bodily after receiving gifts and
hearts. The gestures and utterances of broadcasters are different from gratitude
expression in other activities. That is the particular exchange type in live streaming. For
example, broadcasters have their own gestures and utterances which only appear in live
streaming.
In this study, we noted the number of sequences during observation. One sequence in
living streaming consists of one or several interactions of broadcasters and viewers of
the same topic. The open sequence refers to the beginning of a new topic. And the
continue sequence is the continuing conversation of the same topic as its beginning.
Sequence closes before the topic was changed.
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Patterns of communication in live streaming——A comparison of China and the United States
3.1.3 Feedback
In order to ensure that communication is going successfully and interlocutors have
shared understanding, there is a system of communicative feedback (Allwood, 2010).
Communicative feedback can be explained in broad sense or in narrow sense.
Communicative feedback (narrow sense) refers to unobtrusive (usually short) vocal or
body expressions whereby a recipient of information can inform a contributor of
information about whether he/she is able and willing to (i) communicate (have contact),
(ii) perceive the information (perception), and (iii) understand the information
(understanding). In addition, (iv) feedback information can be given about emotions
and attitudes triggered by the information, a special case here being an evaluation of
the main evocative function of the current and most recent contributions (Allwood,
2008a). Studies of feedback usually use the concept of narrow sense, because the
narrow sense can help scholars focus on ways of giving and perceiving feedback and
functions of feedback, etc.
In this study, feedback is used in its broad sense. “Feedback” (broad sense) refers to the
fact that speaker as well as listener, in a conversation must know how the other party is
reacting (Allwood, 1999b). The interlocutors need to know whether the information is
perceived and understood by each other. The speaker also needs to know how the
listener reacts to what is being said (Allwood, 1999b). From above, feedback in broad
sense contains not only willingness, perception, understanding and emotion, but also
the replies to what is being said. In this study, we analyze patterns of communication in
living streaming from a broad sense, including analyses from many aspects, such as
turn management, feedback, sequence, etc. Using the broad sense of feedback in the
study can cover more information and can describe feedback from a broad view.
Feedback of broad sense helps us give a comprehensive communication patterns in live
streaming.
The main ways of giving feedback linguistically are body feedback, e.g. head
movement or smile (Jensen, 2014), and spoken feedback such as “yes”. Spoken
feedback can be feedback words like “yes, no, m” with various phonological and
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Patterns of communication in live streaming——A comparison of China and the United States
morphological operations allowing expansion of these words, repetition of words in a
previous utterance to show agreement or to elicit confirmation or more information,
and pronominal or other types of reformulation (Allwood, 1999a). In this study, spoken
feedback also includes main massages in replies.
Thus, in this study, we are mainly studying “feedback in a broad sense”, it contains the
main reply to interlocutors. To be more specific, the feedback of the broadcasters was
been operationalized as the body and linguistic reply to the comments, questions and
gifts, hearts. The feedback of the viewers was been operationalized as the comments,
questions, gifts, and hearts.
3.2 Multimodal Communication
According to Allwood (2008c), multimodal communication = co-activation, sharing
and co-construction of information simultaneously and sequentially through several
modes of perception (and production) (Allwood, 2008c). The basic reason for studying
multimodal communication is that it provides data for more complete studies of
“interactive face-to-face sharing and construction of meaning and understanding”
(Allwood, 2008c). In this study, multimodal communication is also important to help
understand communication patterns in live streaming.
Many multimodal communication studies focus on face-to-face communication. That
is because face-to-face communication is the chief representative of multimodal
communication in our lives. Normal face-to-face communication is multimodal, it
employs several modalities of production and perception in order to share information
(Allwood, 1998). According to Allwood’s analyses, the two primary modes of
production are speech and various types of body gestures; the two primary modes of
perception are, accordingly, hearing and vision. The spoken message normally
predominates, while body gestures provide additional information; gestures are often,
in turn, reinforced by prosody. (Allwood, 1998).
A term closely linked to multimodal communication is “modality”. The term “modality”
24
Patterns of communication in live streaming——A comparison of China and the United States
can be used in many ways, but the definition adopted here is that “multimodal
information” is information pertaining to more than one “sensory modality” (i.e., sight,
hearing, touch, smell or taste) or to more than one “production modality” (i.e., gesture
(be used in the sense of any body movement), speech (sound), touch, smell or taste)
(Allwood, 2008c). These are the traditional five sense modalities and their production
modalities.
In multimodal communication, multimodality give us flexibility in the choice of
modality, and also the possibility of being redundant when this is needed, for example,
in a complex noisy environment (Allwood, 2013). Especially, flexibility is very
characteristic of multimodal communication. In many different contexts, the flexibility
of choice can help to improve the efficiency of communication. It reflects one of the
advantages of multimodal communication.
3.2.1 Dimensions of Production and Perception in Multimodal Communication
In Allwood’s study (2013), besides the basic five senses and their corresponding
production modality, he gave an overview of how dimensions of production and
perception can be related in multimodal communication (Table. 1).
Table. 1 Multimodal face-to-face communication—Perception and production
This table displays how different modalities are produced and perceived through
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Patterns of communication in live streaming——A comparison of China and the United States
different media. It is clear that multimodal communication production basically
includes two aspects: speech (prosody, vocabulary, grammar) and gestures (body
movements, posture, etc.) Therefore, besides the auditory aspects of speech, there are
also other types of communicative expression (Allwood, 2013), e.g. facial gestures,
posture, etc. In fact, all of 15 types of body movements (Allwood, 2002) may be used/
analyzed in multimodal communication.
3.2.2 Body Movements
Allwood (2002) discussed 15 major types of body movements from the perspective of
production. They are: Facial gestures, Head movements, Direction of eye gaze and
mutual gaze, Pupil size, Lip movements, Movements of arms and hands, Movements
of legs and feet, Posture, Spatial orientation, Clothes and adornments, Touch, Smell,
Taste, Nonlinguistic sounds. Each type is followed by an account of its functions. These
functions given are meant as examples.
He also noted that the majority of the body movements are connected with visual sense,
while touch is connected with the sense touch and hear with auditory sense. Smell and
taste are in ordinary language more or less neutral with regard to production and
perception (Allwood, 2002).
The categories of body movements and analyses of functions provide a significant basis
for classifications and analyses of body movements in live streaming. In addition,
because Allwood’s study was based on face-to-face communication, it gives an
opportunity to make comparisons of body movements between face-to-face
communication and live streaming communication.
Allwood (2002) also claimed that body movements can be used both together with
speech and independently of speech. Communicative expressions over and above
auditory aspects of speech can supplement auditory aspects of speech or play an
autonomous role in communication (Allwood, 2013).
There are studies focused on this aspect. Allwood and Ahlsén (2009) studied features
of gesture types that are produced before or simultaneously with speech. They found
26
Patterns of communication in live streaming——A comparison of China and the United States
that most of the factual information gestures are produced simultaneously with the
target words.
Allwood and Cerrato (2003) studied gestures related to verbal feedback expressions,
their results showed that feedback is mostly expressed simultaneously by vocal/verbal
and gestural means. Specially, the gestures accompanying verbal and vocal feedback
expressions can be broadly categorized according to their function in the given context
(Allwood & Cerrato, 2003). In addition, they also claimed 4 ways about how gestural
feedback expressions modify the meaning of the vocal/verbal expression:
reinforcement (R), adding redundancy by giving the same information as the vocal
message; positive (P), indicating a positive reinforcing attitude; negative (N),
weakening what has been said vocally; contradicting (C), contradicting what has been
said vocally.
These studies show that body movements are a major source of the multimodal and
multidimensional nature of face-to-face communication. They offer us a new angle
when analyzing body movements in live streaming, especially how body movements
are used with vocal/verbal expressions in live streaming.
Multimodal communication studies in face-to-face communication provide us with
ideas for observing and analyzing multimodal communication in live streaming. They
not only demonstrate dimensions of production and perception in face-to-face
communication, but also show the importance of body movements in multimodal
communication. All of these can help us build a theoretical framework to analyze
multimodal communication in live streaming.
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Patterns of communication in live streaming——A comparison of China and the United States
4. Methodology
In this section, the study design, data from analysis and ethical considerations that are
relevant to this study are described.
4.1 Study Design
4.1.1 Observation and Coding Framework
Observation and analysis are the main methods of this study. We engaged in a pre-study
by watching some live streaming videos and analyzing some features of it before
constructing the observational schema and unifying the coding standards.
Observation, as a main method of collecting data in this study, helps us directly see both
broadcasters’ and viewers’ interactions. However, observation sometimes can be
subjective because of different observers. Therefore, the data of observation is gathered
by same coding standards in order to reduce the subjective impact. So the data is more
valid in analysis. Through observation, we can also include some other features which
were unpredicted in pre-study.
Based on the pre-study and theoretical framework of this study, observation framework
(Appendix. 1) mainly includes three parts:
(i) Basic information of a live streaming video: serial number; category; content;
platform; watching time; watching duration; number of viewers; broadcaster’s ID, age,
gender, and dressing up; broadcasting place; broadcasting place movement. Through
these scales, demographic characteristics of the broadcasters and other basic
information of live streaming are considered in our analysis.
(ii) Scales to measure the interactivity of live streaming:

Number of feedback units: the feedback broadcasters give to the viewers’ comments
and questions.

Number of (viewer’s) questions: the questions from viewers.

Number of (broadcaster’s) answers: the answers given by broadcasters.
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Patterns of communication in live streaming——A comparison of China and the United States

Number of sequences: the sequence changing times (according to the description
in theoretical framework section).
(iii) Features of multimodal communication in live streaming: the modalities used in
live streams. Specially, we focus on body movements in multimodal communication in
live streaming. The main categories of body movements (based on 15 types of
Allwood’s study) and their functions are particularly noticed.
Besides, some other details not belonged to these three parts are recorded in the
exception part. The findings are discussed in results and discussion section.
Taking the 18th live streaming videos in China as an example, we coded it as following:
(i) Basic information of a live streaming video:
Serial Number: A18; Category: Music; Content: Singing and chatting (asking for gifts
and other random topics); Platform: Yizhibo; Time (0:00-24:00): 2017/4/17 16:25;
Duration (mins): 23; Number of viewers: 136000;
Broadcaster’s ID: ZDJ; Gender (not sure=0,Female=1, Male=2, multi-gender=3): 1;
Age (not sure=0, 0-20=1, 20-30=2, 30-40=3，>40=4): 2;
Place (Indoor=1, Outdoor=2): 1; Place (specific): Bedroom; Place changing
(change=1, not change=2): 2; Dress up (exposed=1, unexposed=2, not sure=3): 3;
(ii) Scales to measure the interactivity of live streaming:
Number of Feedback units: 68; Number of Questions: 22; Number of Answers: 8;
Number of Sequences: 10;
(iii) Features of multimodal communication in live streaming:
Multimodal Communication (sending information): Face, gesture, voice; say and sing
“I love you” while wink and smile;
Bodily Movements: Wink, movements of arms and hands (finger point at the camera),
facial gestures (laugh);
(iv) Exceptions: Broadcaster uses laugh as feedback, but the audience can’t know which
comment she laughs; the audience interact with each other frequently; broadcaster reads
29
Patterns of communication in live streaming——A comparison of China and the United States
the comment out but don’t know its meaning (several times); someone asked “how is
your lips?” the broadcaster doesn’t reply, but wipes her lips.
4.1.2 Types of Live Streaming to Be Observed
After constructing the observational framework, we started selecting the live streaming
videos by classifying the types of live streaming to be observed in this study.
The types of live streaming are decided by combining types on different live streaming
platforms. We summarize the classifications and find that, in general, they include 9
types of live streaming: chat, talk show, music, food, travel, sports, game, news, and
activity.
“Chat” refers to talking randomly without a specific topic, while a “talk show” has a
specific topic and usually has only one topic. “Music” refers to singing, dancing, or
playing instruments by broadcasters. “Game” live streaming is usually showing the
skills of playing computer games in real-time. “Travel” live streaming is about
attractions or showing sceneries during travels. “Activity” is live streaming
broadcasting events or activities like concerts, meetings, press conference etc. “Food”
refers to making food or teaching cooking. “Sports” live streaming is usually about
broadcasting sport games and fitness.
Our observations cover all these 9 categories in both two countries. During observations,
in total, we watched 106 live streaming, 54 of USA (8 chat, 8 talk show, 8 music, 4 food,
6 sports, 6 travel, 6 games, 4 news, 4 activity) and 52 of China (8 chat, 8 talk show, 8
music, 4 food, 5 sports, 5 travel, 6 games, 4 news, 4 activity). Each live streaming
videos was watched for 20 to 30 minutes, the total length is 2251 minutes (1088 minutes
of American live streaming, 1163 minutes of Chinese live streaming).
Live streaming from China and USA in this study means that the broadcasters are
Chinese or Americans. During studies, in order to confirm the nationality of
broadcasters, we referred to their Twitter, Facebook or other information showing the
nationality of the broadcasters. This provides a better basis for a comparative study of
China and the USA.
30
Patterns of communication in live streaming——A comparison of China and the United States
4.2 Data Analysis
Qualitative and quantitative analysis are both used to analyze the data.
Microsoft Excel 2013 and IBM SPSS Statistics 23 are used in quantitative analysis. By
inputting data into Excel, we used IBM SPSS Statistics 23 to process the quantitative
data. All of quantitative data form 106 samples in this study are valid to analyze in
statistics. Z-score is used to process data as standard scores. Then SPSS is used to check
the normality of data in continuous variables of both countries. Some data not according
with normal distribution are processed into normal distribution. After normal
processing, data in accordance with normal distribution can be analyzed by Cluster
analysis and Pearson correlation analysis. Then we examine the reliability and validity.
Cronbach’s alpha of the 106 samples data of the 6 scales measuring interactivity
(Number of feedback units, number of questions, number of answers, number of
sequences, feedback per minute, and answer rate) are higher than 0.7 in our study. This
means the data in this study has acceptable reliability.
In addition, when doing quantitative analyses, we added two calculated quantitative
scales. The calculation of these scales is as following:
•
Feedback per minute: Divide number of feedback by duration (minutes).
•
Answer rate: Divide number of answers by number of questions.
This is because each live streaming has its own observational duration. Feedback is
very sensitive to observational duration. So we calculate feedback per minute as a new
variable. Answer rate are also calculated to measure the interactivity of live streaming.
Qualitative analysis in this study is mainly combining the features of live streaming
with the relevant theories. ICM theory is used to analyze features of interactivity in live
streaming which we recorded in study. Multimodal communication theory is used to
analyze characteristics of multimodality in live streaming communication. For instance,
we analyze traits of body movements in live streaming by connecting some features we
recorded with Allwood’s 15 types of body movements.
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Patterns of communication in live streaming——A comparison of China and the United States
4.3 Ethical Consideration
During the data collection and analysis processes, there are ethical considerations we
have to take note of this study. First, the live streaming we observed is open to all users.
We did not observe live streaming only friends can see. Second, to protect the privacy
of broadcasters, all personal information in the study is kept confidential. All names of
broadcasters are anonymous or mentioned with nicknames during analyses. Third, all
the data is just used in academic research and will not be used in business.
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Patterns of communication in live streaming——A comparison of China and the United States
5. Results and Analyses
In this part, demographics of broadcasters, broadcasting place and place movement,
numbers of viewers, interactivity and multimodal communication in live streaming are
studied through analyzing the observational data. Comparisons of China and the USA
are also demonstrated in this section.
5.1 Overview of the Observation Data
During April, 2017, 106 live streams are observed in both China (52) and the United
States (54) in this study. We observed 20 to 30 minutes per live stream in most live
streaming, 2251 minutes (37.52 hours) in total. The live streams we observed are picked
randomly but trying to cover as many types of live streaming as possible.
5.1.1 Demographics of Broadcasters
Age
Cumulative
Frequency
Valid
Percent
Valid Percent
Percent
Not sure
26
24.5
24.5
24.5
0-20
3
2.8
2.8
27.4
20-30
48
45.3
45.3
72.6
30-40
16
15.1
15.1
87.7
Over 40
13
12.3
12.3
100.0
Total
106
100.0
100.0
Table. 2 Age distribution of broadcasters in all samples
In the 106 samples, there are 62.3% male broadcasters, a little bit more than female
broadcasters. We also noted the age of broadcasters by the same way as confirming
their nationalities, through their talks in live streaming or their social platforms, such
as Facebook and Twitter. As for the age distribution (Table. 2), 45.3% of broadcasters
are young people, between 20 to 30 years old. If we remove 26 samples of uncertain
age, there are 60% of broadcasters from 20 to 30 years old. Young people show higher
33
Patterns of communication in live streaming——A comparison of China and the United States
receptivity for live streaming than elder people. Children may not have that much time
and freedom for using live streaming. People who are 20 to 30 years old are at age to
explore and expand the social network. Also, they usually do not have a family to care
of, living alone. So they are free after school or work. Because of these reasons, people
from 20 to 30 are the main groups of people to broadcast themselves. This demographic
feature appears to both China and America.
5.1.2 Place Broadcasting
Correlations
Place
Place
Spearman’s rho
Place
1.000
-.726**
.
.000
106
106
-.726**
1.000
Sig. (2-tailed)
.000
.
N
106
106
Correlation Coefficient
Sig. (2-tailed)
N
Place movement
movement
Correlation Coefficient
**. Correlation is significant at the 0.01 level (2-tailed).
Place（Indoor=1，Outdoor=2）, Place movement (move=1，not move=2）
Table. 3 Correlations between place and place movement
Viewing all 106 samples, 76.4% broadcasters (81) broadcast indoor. And 84%
broadcasters (89) just stay in one place, only 16% of them keep moving and changing
places during broadcasting. In order to test whether place they broadcasting and place
movement are correlated, we use Spearman’s rho to test these two variables. As Table.
3 shows, the correlation is significant at the 0.01 level (2-tailed). And the correlation
coefficient is -0.726 (|-0.726|>0.7), which means they have strong correlation. Number
1 of place represents “indoor” and 2 represents “outdoor”, but number 1 of place
movement represents “move” and 2 represents “not move”, so the correlation
coefficient is minus. The correlation means broadcasters who broadcast indoor usually
do not move to another place, and broadcasters who broadcast outdoor usually change
place during broadcasting. This result is based on the whole 106 samples, so it’s valid
34
Patterns of communication in live streaming——A comparison of China and the United States
in both China and the United States.
Based on observations, several reasons are concluded to explain this phenomenon. First,
broadcasters can connect WIFI indoor, but they need to use 4G outdoor. The WIFI
signal outside is not that stable and fast as inside WIFI. And 4G sometimes costs a lot
of telephone charges. Second, indoor environment is much better than outdoor, less
noise, less sunshine reflecting light and less other interference factors. In a better
environment, broadcasters can focus more on broadcasting and give more feedback.
For example, Jie (from America) was broadcasting on Brooklyn Bridge on a shining
day wearing a pair of sun glasses, she walked slowly because it was crowded on the
bridge. She cannot reply immediately and even cannot see all the comments and
questions. After a while, she apologized:
“I can’t reply to you sometimes and I can’t see your words clearly because of the
sunshine and I’m walking. Oh, my god！It’s too crowded today.”
There are the different categories of live streaming, and we found that the live streams
broadcasted outdoor are usually about travel, news and activity. In these three kinds of
live streaming, broadcasters need to walk around to broadcast what is happening at the
time.
5.1.3 Number of Viewers
The number of viewers in China and the United States is very different. On average,
there are 859.74 viewers per live stream in USA, and there are 371281.69 viewers per
live stream in China. This is not only explained by the difference in population. The
population of China is 4.31 times of America, but the number of live stream viewers is
432 times greater than in the USA.
This is a big difference between the viewers’ in the two counties. The explanation was
be given by commercial interests and psychological needs. Yi Jia (2016) described the
core of live streaming as interpersonal interaction under the commercial interests.
Aiqing Yuan and Qiang Sun (2016) warned that as a commercial force driven product,
35
Patterns of communication in live streaming——A comparison of China and the United States
live streaming still keeps the purpose of pursuing interests.
According to the Statistical Report on Internet Development in China (2017), there are
more than 200 live streaming platforms and 344 million users (47.1% of Internet users
of China) of live streaming till January of 2017. As some big American Internet
companies joined the live streaming market in the United States, several large Chinese
Internet companies also joined the Chinese live streaming market. The companies know
the psychological needs of the consumers well.
Different from most of American living streaming platforms, most Chinese live
streaming platforms provide high-level users lots of privileges, such as different titles
and colors of their usernames. So broadcasters can easily recognize the high-level
viewers’ comments from the huge number of comments. A quick way to become a highlevel user is sending gifts to broadcasters. And all of the gifts are virtual and only sold
on the platforms they use. After broadcasting, broadcasters can get some money from
platforms according to the gifts they get. In this way, platforms sell gifts to viewers and
share incomes with broadcasters, so companies holding these platforms earn a lot.
Viewers who send gifts can get the special effects on screens and a “Thank you dear!”
from broadcasters with inner satisfaction.
Besides commercial and psychological reason, technological improvement also helps
the development of live streaming. In 2016, there were 469.2 million users using mobile
payment in China. This convenient payment method helps viewers buy gifts whenever
they want.
As for broadcasters, broadcasting becomes a new occupation with hundreds of
thousands RMB per day in China (Yi Jia, 2016). After it changes to an occupation,
broadcasters need to attract viewers and fans because they live by broadcasting. But
most of broadcasters in America still broadcast for fun or just killing time.
All of the above are main differences between China and the United States, and cause
the huge difference of number of viewers in these two countries.
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Patterns of communication in live streaming——A comparison of China and the United States
5.1.4 Interactivity in China and the USA
Descriptive Statistics
N
Minimum
Maximum
Mean
Std. Deviation
Number of Feedback units
52
0
138
36.58
28.329
Feedback per minute
52
.00
4.60
1.6420
1.21472
Number of Questions
52
2
166
25.60
28.395
Number of Answers
52
0
37
10.31
8.264
Answer Rate
52
.00
1.00
.5195
.31263
Number of Sequences
52
0
94
20.42
22.346
Valid N (listwise)
52
Table. 4 Descriptive statistics of interaction data of China
Descriptive Statistics
N
Minimum
Maximum
Mean
Std. Deviation
Number of Feedback units
54
0
100
26.37
26.968
Feedback per minute
54
.00
4.15
1.3369
1.31711
Number of Questions
54
0
81
18.67
20.805
Number of Answers
54
0
59
7.81
11.783
Answer Rate
54
.00
1.19
.3792
.35211
Number of Sequences
54
0
56
12.57
14.458
Valid N (listwise)
54
Table. 5 Descriptive statistics of interaction data of USA
In the last part of data overview, 6 significant factors given below are discussed and
compared in China and the USA. The 6 factors are: Number of feedback, feedback per
minute, number of answers, answer rate and number of sequences (decided mainly by
broadcasters), while the number of questions (mainly decided by the viewers).
Combining these two aspects, interactivity can be measured comprehensively.
From Table. 4 and Table. 5, concerning all the 6 factors, China has higher mean than
the USA. For example, the mean of “number of feedback units” in China is 36.58, while
it is 26.37 in the USA. Standard deviations are similar in both countries except the
number of questions and the number of sequences that are different. The standard
deviation of “number of questions” in China is 28.395, while it is 20.805 in the USA.
Comparing the max value of the two factors in both countries, standard deviations are
37
Patterns of communication in live streaming——A comparison of China and the United States
influenced by the extreme value. For example, the maximum number of questions in
the USA is 81while it is 166 in China. This extreme value is much higher than its mean
value, so the standard deviation of “number of questions” in China is much higher than
its in the USA. In the other four factors, they have similar standard deviations, so they
have similar dispersion degrees. Assuming that 54 samples from the USA and 52
samples from China are representative, we can say Chinese live streaming was stronger
interactivity than live streaming in the USA.
The reasons for the differences in interactivity need to be analyze data. First, in China,
there are many more viewers than in the USA. From this aspect, more viewers can
interact with broadcasters. They may comment more and ask more questions. But high
interactivity of viewers not equals to high interactivity of broadcasters. Broadcasters
need motivation to interact with viewers. In USA, broadcasters are the center of live
streaming, most of them broadcast for enjoy themselves. However, in China, some of
the broadcasters broadcast for commercial benefits, some even make a living by
broadcasting. So viewers are the center of broadcasting. Broadcasters need to attract
viewers’ attention. This makes them more interactive. And if viewers feel they are
concerned, they may stay and become fans of the broadcasters. Giving feedback is the
only way broadcasters have of making their viewers feel concerned. So from the
broadcasters’ aspect, Chinese broadcasters have stronger motivation to give feedback.
After getting feedback and seeing others getting feedback, viewers may have more
willingness to comment or ask questions. All of these reasons can explain why Chinese
live streaming seems to have higher interactivity than American live streaming.
5.2 Interactive Communication Management
Communication is based on the interaction of the interlocutors. Different patterns of
communication have different ways to manage interactions. Interactive communication
management (ICM) provides a framework to analyze the interaction of communication.
ICM has three subsystems, turn management, feedback and sequences. In this section,
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Patterns of communication in live streaming——A comparison of China and the United States
we go through these subsystems and analyze the patterns of ICM in live streaming.
5.2.1 Turn Management
In live streaming communication, there are usually one broadcaster and many viewers
and broadcasters seems have absolute authority in the communication in live streaming.
This is different in comparison with face-to-face communication, where all participates
may get turn. Here we will study three issues of turn management: who can get turn,
how do they get turn, and who really control the turn.
Correlations
Number of question
Number of
Number of
question
answer
Pearson Correlation
1
Sig. (2-tailed)
N
Number of answer
.699**
.000
54
54
Pearson Correlation
.699**
1
Sig. (2-tailed)
.000
N
54
54
**. Correlation is significant at the 0.01 level (2-tailed).
Table. 6 Correlations between question number and answer number in USA
Taking live streaming in USA as an example, using the method of Pearson correlation
(Table. 6), correlations between question number and answer number is significant at
the 0.01 level (2-tailed) and the correlation coefficient is 0.699. Processing data of
China can get the same results. In both countries, question number and answer number
are correlated.
To explain these correlations, we cannot just analyze from one side. Questions and
answers promote mutually and co-construct the whole interactive communication.
Specifically, viewers raise questions and broadcasters have questions to answer. But if
broadcasters do not answer any questions, viewers probably will not like to ask any
more. The interactivity may decrease to a low level or stop totally. So answering
questions also leads more questions coming up. Therefore, answering question is
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Patterns of communication in live streaming——A comparison of China and the United States
necessary and important for broadcasters. For example, when broadcasting activities,
there were comments and questions at first. But if the broadcaster did not give any
feedback, then “there was silence in the broadcasting world”. Even if some new comers
may give comments continuously, they soon keep silent, too.
Therefore, broadcasters and viewers are the co-constructors of the interaction. So
viewers can get the turn from raising questions and comments. And broadcasters seem
to hold the turn all the time, except when viewers are commentating or asking.
Broadcasters need to read at such a moment, so viewers actually get the turn then.
Broadcasters can get the turn back from choosing questions and comments, and then
give feedback.
Correlations
Zscore:
Zscore:
Feedback per
minute
Feedback per
Zscore:
minute
Answer Rate
Pearson Correlation
Sig. (2-tailed)
N
Zscore:
1
Answer Rate
.000
52
52
**
1
Pearson Correlation
.607
Sig. (2-tailed)
.000
N
.607**
52
52
**. Correlation is significant at the 0.01 level (2-tailed).
Table. 7 Correlations between feedback per minute and answer rate in China
Taking live streaming in China as an example, from Pearson correlation in Table. 7,
correlations between feedback per minute and answer rate is significant at the 0.01 level
(2-tailed) and the correlation coefficient is 0.607. Processing the data of USA can get
the same results and even higher correlation coefficient.
In both two countries, feedback per minute and answer rate are correlated. If
broadcasters want to communicate with viewers, the feedback per minute and answer
rate result are in high scores. But if broadcasters have less willingness to communicate
and do not want to give feedback, the two factors can be low. Broadcasters have the
absolute power in live streaming. They can choose whether to give feedback or answer
the questions.
40
Patterns of communication in live streaming——A comparison of China and the United States
To conclude, broadcasters are powerful interlocutors who control the turn. They can get
the turn by starting a new topic, giving feedback and answering the questions they want.
But they lose turn when they see the comments and questions without talking. Viewers
can get the turn by asking questions or giving comments.
5.2.2 Feedback
Feedback processes help interlocutors communicate successfully, making sure that they
have contact, perceive and understand each other’s emotional-attitudinal reactions and
contributed content (Allwood, 2013). Viewers use comments and questions showing
whether they can receive information from broadcasters. Sometimes sending gifts also
can be interpreted as feedback. The feedback ways are simple for viewers. Broadcasters
can only get the information from these ways. Broadcasters give gestures or answers to
comments and questions as feedback. Their feedback is multimodal. Gestures like
nodding, facial gestures (smiling, frowning etc.), moving close to camera can be
interpreted as feedback in body movements. Answering to comments and questions is
the verbal way of feedback. Emotional-attitudinal reactions of broadcasters can be
found in both gestural and verbal ways.
Broadcaster sometimes may ask for feedback from viewers. During live streaming,
broadcasters just face the cameras and see the comments and questions rather than the
viewers’ face. Broadcasters may feel insecure if viewers do not give feedback, they
even ask if the network is broken down. So sometimes broadcasters may ask for
feedback. For example, an American policy broadcaster Jos said:
“Can you see me? Can you hear me? Raise your hands if you hear me. Raise your
hands! Raise hands!”
Viewers comment hands emoji to give feedback.
“Ok! We can keep going on then. What I just said…”
Viewers’ feedback in live streaming can be ignored, interrupted, delayed, and vague
(lack of understanding). Viewers give lots of comments and questions, broadcasters can
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Patterns of communication in live streaming——A comparison of China and the United States
only reply to some of them, especially what they are interested. In this situation, some
comments and questions can be ignored. Broadcasters (from China and the USA) often
ignore some rude and aggressive comments, they even block the users who give those
comments. Blocking (the blocked user cannot commented in the live streaming
anymore) can be interpreted as a special feedback.
From the previous study, the share of interrupting feedback shows if the participants
interrupt each other frequently, e.g. because the interaction is fast (Ahlsén et al, 2003).
The various speed of interaction in different groups of live streaming shows a big
difference between China and the USA. We use cluster analysis to discuss the
differences in detail. In general, interactions in live streaming are fast. Because usually
there is just one broadcaster communicating with lots of viewers simultaneously.
Comments and questions are coming all the time during broadcasting, so broadcasters
have to read them while talking. Sometimes they are attracted by comments, so their
talking can be interrupted. As for delayed answers and vague feedback in live streaming,
they are discussed in detail in discussion section.
Our analysis of interactivity in China and USA above shows that interactivity in China
is higher than interactivity in USA. If we analyze this more in detail by comparing
different types of live streaming in the two countries, there are obvious differences and
similarities between China and the USA. In order to compare the interactivity of
different categories from China and the USA, we use cluster analysis to divide live
streaming video into different categories based on degree of interactivity. The cluster is
also based on the 6 factors used in the descriptive comparisons. The results of cluster
analysis are introduced respectively. As mentioned, these 6 factors are divided into
broadcaster interactivity factors and viewer produced interactivity factor. The
broadcaster factors measure feedback from broadcasters’ side, while the viewer factor
measures feedback from viewers’ side. So we can describe feedback more in-depth
levels from both sides by analyzing this cluster analysis.
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Patterns of communication in live streaming——A comparison of China and the United States
Table. 8 Dendrogram of live streaming in China
According to the dendrogram in Table.8 (also the cluster membership in Appendix 3),
43
Patterns of communication in live streaming——A comparison of China and the United States
we divide all 52 live streaming videos into three groups. In group 1, chat and talk show
are the main categories. Music and food appear much in group 2. And sports, travel,
news, game and activity belong to group 3. By analyzing the categories in different
groups, we come up with three names of the groups. Chat and talk show are all about
talking. Broadcasters keep talking to the viewers. So we call group 1 talking live
streaming. Group 2 mainly consists of music and food. Broadcasters display their
singing, dancing, instruments playing, and food cooking skills. Besides, they also pay
much attention to talk to the viewers. So group 2 is called display-talking live streaming.
Group 3 consists of sports, travel, news, game, and activity five categories. In these five
categories, broadcasters focus on display rather than talking and there might even be no
talking in the whole broadcasting. So group 3 is called display living streaming. 3
groups of live streaming appear different degrees of interactivity. Group 1 has the
highest interactivity, group 2 is in medium level, and group 3 interacts less than other
groups. The different levels of interactivity relate to the categories of live streaming.
Group
Original categories
Group name
1
Chat, Talk show
Talking live streaming
2
Music, Food
Display-talking live streaming
3
Sports, Travel, News, Game, Activity
Display live streaming
Table.9 Groups of live streaming in China
Talking live streaming is focused on talking. More accurately, it is focused on the
talking of broadcasters and comments and questions from the viewers with high level
of interaction. Some of the broadcasters even do not have specific topics, just choose
the questions and comments which they want to answer. In this situation, viewers
actually hold turns and partly control the topic of live streaming. When broadcasters
have their own topic for the broadcasting, they keep talking but can easily be interrupted
by the feedback from viewers. In talking live streaming, the viewers are almost the only
focus of broadcasters. Broadcasters keep interacting with viewers. And because of the
high dependence of viewers, feedback in talking live streaming has the highest level in
44
Patterns of communication in live streaming——A comparison of China and the United States
all three types of live streaming.
In live streaming, broadcasters cannot see the faces of viewers like face-to-face
communication, they can just “see” the viewers by their feedback with their usernames.
The feedback from viewers represents the viewers by showing their attitudes and
thoughts. Feedback from the broadcasters said is the main way for them to know their
viewers. Broadcasters give feedback to keep interaction with viewers and keep live
streaming going on.
Broadcasters of display-talking live streaming have more foci than talking live
streaming. Broadcasters focus on displaying their music and food making procedures
to viewers while answering related questions and replying comments. When
broadcasters are displaying, they usually do not have time to interact with viewers, even
cannot see the feedback from viewers. In order to solve this problem, broadcasters
usually stop their display and spend some time replying to the questions and comments
from viewers and then come back to display their work. Mixing displaying and replying
for every several minutes help broadcasters get feedback and give feedback. Sometimes,
broadcasters can interact with viewers while displaying. But this distraction usually
slows their work down or causes a little pause during working. Some singers use smiles
to give feedback while singing during broadcasting, but viewers cannot know which
comments the broadcasters are replying. To conclude, display-talking live streaming
has a medium level of interactivity and less feedback than talking live streaming.
Display live streaming is mainly focused on displaying rather than interaction and even
no interaction. This group have categories of game, travel, news, sports, and activity.
When broadcasters broadcast these things, they show the skills of playing computer
games, great sceneries, situations of news, sports games and activities in real-time.
Some broadcasters may have interaction with viewers where there are pauses during
activities. Some broadcasters do not give any feedback during the whole observation
periods. So, display live streaming have the lowest interactivity with no feedback
sometimes.
After analyzing the three groups of live streaming in China, we do the same cluster
analysis of the data in USA and we get the cluster membership shown in Table.10. The
45
Patterns of communication in live streaming——A comparison of China and the United States
factors and the methods are same as China, so we have same standards in both countries.
Table. 10 Dendrogram of live streaming in USA
46
Patterns of communication in live streaming——A comparison of China and the United States
According to the dendrogram (also the cluster membership in Appendix 2) above, we
divide live streaming video into groups. If we divide into the same 3 groups as China,
there are only a few samples are in group 2. The group 2 has a few representative, and
this loses its meaning. So we divide the samples into 2 groups. As Table.11 showing,
group 1 has chat and music and group 2 consist of food, talk show, sports, travel, news,
game, and activity. Combining features of the data, we name group 1 as two-way
interaction live streaming, and group 2 as one-way interaction live streaming.
Group
Original categories
1
Chat, Music, Interactive travel
2
Food, Talk show, Sports, displaying
Group name
Obvious two-way interaction live streaming
Obvious one-way interaction live streaming
travel, News, Game, Activity
Table.11 Groups of live streaming in USA
Group 1, as its name, shows obvious two-way interactivity in live streaming. In most
of the broadcasting time, broadcasters pay attention to viewers and give feedback all
the time. Different from the talking live streaming with the highest interaction in China,
music and interactive travel are included in highest interaction group. As mentioned,
viewers in China are over 400 times than viewers in USA. Broadcasters in China
seldom meet situations of no comments and questions to give feedback. But American
broadcasters often face this situation, they cannot keep interact with the viewers without
pauses. So during the same time period, Chinese broadcasters have more feedback,
more questions to answer and answers, and a higher answer rate. And even if American
broadcasters broadcast for chatting, because of the limited comments and questions
from the viewers, the number of feedback, questions, answers, and answer rate are
limited. So the data of interactivity of chat are similar to the data of music and
interactive travel. When broadcasters play the instruments or show the sceneries,
sometimes, they are also waiting for the comments and questions. So in the group of
obvious two-way interaction, the interactivity is highest in USA but lower than in
talking live streaming of China.
47
Patterns of communication in live streaming——A comparison of China and the United States
Group 2 contains 7 categories, food, talk show, sports, displaying travel, news, game,
and activity. These live streams show obvious one-way interactivity characteristics.
Broadcasters keep talking or showing viewers about their skills, sceneries, and activities
but seldom give feedback or do not give feedback. Broadcasters have a low dependence
on their viewers. So in the group of obvious one-way interaction, the interactivity is
low in all 7 categories.
Sometimes in news, sports, and activities live streaming, broadcasters cannot see the
comments and questions. They may just put cellphones somewhere and letting it
broadcast. When the affairs they want to broadcast are finished, they press the button
to end the live streaming. Live streams about food and displaying travel focus on
displaying the food making procedures or the sceneries. Broadcasters pay more
attention to what is displayed than interaction. Broadcasters broadcasting playing
computer games have no interaction with viewers because they are just showing their
skills to the viewers. Most of the game broadcasters are professional broadcasters, and
they make a living by playing games. Broadcasting is one way for them showing their
skills and they can also get money by support from the viewers. The games are often
very fierce, so they need to focus on the games and have no time to interact with viewers.
Viewers always discuss with each other by using the comments function in this
situations. The number of viewers of games are extremely large and the interaction
between viewers to viewers keeps all through the broadcasting. In China, game
broadcasters have similar characteristics as American broadcasters, but they sometimes
interact with viewers.
The biggest difference between China and USA in interactivity appears in the talk show.
In China, the talk show is in the group with the highest interactivity. But in USA, the
talk show is in the group of obvious one-way interaction live streaming, which has low
interactivity. American talk show broadcasters share their own opinions to viewers
more, so they have limited time to give feedback to viewers. Viewers also express
themselves less. But in China, talk show broadcasters prefer to discuss the topics with
the viewers. They keep receiving feedback and giving feedback about the topic. So talk
shows in China are co-constructed by broadcasters and viewers. Therefore, talk shows
48
Patterns of communication in live streaming——A comparison of China and the United States
in China have the highest level of interactivity, while talk shows in USA have a low
level of interactivity. The difference can be partly attributed to cultural influence.
According to Hofstede, the culture of the United States emphasis individualism, while
Chinese culture is more collectivism. So American broadcasters may tend to show
themselves more. Chinese broadcasters may prefer to discuss with their viewers. This
could be the reason of the difference of interactivity in the two countries.
5.2.3 Sequence
The sequence in live streaming usually consists of a comment or a question and one
feedback. One sequence in living streaming consists of one or several interactions of
broadcasters and viewers of the same topic. Sequences are usually short, but the number
of sequences are large, which are the main features of sequences in live streaming.
Sequences show strong similarity of live streaming in China and the USA. These
features of sequences are valid in both countries. Because the similar sequences or
exchange types are mainly depended by the new technology. Culture differences do not
have obvious influence in sequence of live streaming. So in this section, we analyze
these common features of sequences in both China and the USA.
Broadcasters face tens to hundreds of thousands of viewers during live streaming. When
many viewers participate in the live streaming, broadcasters need to reply to the
comments and questions. Every feedback to a comment/question and the
comment/question consist a whole sequence or a particular exchange type. Because
broadcasters seldom wait to communicate with the same viewers to continue their
previous sequence. So there are usually many sequence.
In most situations, broadcasters give feedback without following up with a question to
the viewers. But when few viewers comment, broadcasters may have several questionsanswers as one sequence. If broadcasters ask back to the viewers when they replied,
they may wait for viewers’ answer. But speaking is usually faster than typing into words,
so from viewers receiving questions to finishing typing and sending out, there is still
some time. During this time, broadcasters usually wait while answering other questions
49
Patterns of communication in live streaming——A comparison of China and the United States
or replying to other comments.
Mostly the sequence between broadcasters and viewers is one question-answer or one
comment-reply. Because most sequence are short, broadcasters can reply many
questions and comments in short duration. And when broadcasters really need to
interact with viewers, they may reply briefly and then move to the next comments or
questions. Every viewer has his/her own point of view, so the questions and comments
can be quite different. Thus, broadcasters needs to pay more attention on understanding
and replying to them. Also, viewers come and go quickly, as for new viewers, they
know nothing about the topics and the broadcasters, so they may ask some repeated
questions. So as we can see, broadcasters have lots of questions and comments to reply
to. So the number of sequences in live streaming is large.
5.3 Multimodal Communication in Live Streaming
According to Allwood (2008c), multimodal communication = co-activation, sharing
and co-construction of information simultaneously and sequentially through several
modes of perception (and production). The basic feature of multimodal communication
is employing several modalities of production and perception in order to share
information. In this section, we analyze the specific mode of multimodal
communication in live streaming, and then focus on body movements in live streaming.
Flexibility in the choice of modality is also analyzed. Multimodality used in different
contents of live streaming is claimed. Comparisons between China and the United
States are also demonstrated.
5.3.1 Specific Multimodal Communication in Live Streaming
During live streaming, broadcasters can use more than one modalities/channels to
broadcast and communicate with the audience, while the audience can only use limited
ways to communicate with broadcasters. This unique model of communication in live
streaming builds its specific multimodal communication patterns. It can be divided into
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Patterns of communication in live streaming——A comparison of China and the United States
two parts:
(i) For broadcasters, in live streaming, they are both information senders and receivers.
When producing information, they can use more than one channel. Basically, they use
auditory aspects of speech, singing or non-linguistic voice, combined with
communicative body movements (facial gestures; head movements; hand and arm
movements; eyes movements; lips movements, etc.). For instance, one American
female broadcaster chatting with viewers about fitness, shook her head saying “No”
and then made non-linguistic sounds to show her disagreement with some comments.
In addition, internet and live streaming technologies allow them to use more channels
to send information, e.g. computer game interface, videos of conference scene, videos
of concert scene, videos of football game, music, graphics, etc. For example, most
gaming broadcasters only use auditory aspects of speech and game interface to send
information.
On the other hand, broadcasters are also information receivers during communication
in live streaming. However, compared with sending information, broadcasters perceive
information mainly by eyes/visual sense. Because most of the effective information
from viewers is text-based comments and heart-shaped images. In China, broadcasters
can also get gifts sent by viewers.
(ii) For the audience, as the information receivers, they perceive information mainly by
visual sense and auditory sense. All information they get is through screens of
computers or smart phones. Therefore, they depend on eyes and ears to receive what
broadcasters send to them. Meanwhile, viewers are also information senders. As we
mentioned before, they can type text-based comments/questions to have
communication with broadcasters and tap hearts, or send gifts (in China) to sho…