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Public Relations Review 48 (2022) 102174
Contents lists available at ScienceDirect
Public Relations Review
journal homepage: www.elsevier.com/locate/pubrev
Social media engagement with organization-generated content: Role of
visuals in enhancing public engagement with organizations on Facebook
and Instagram
Ganga Dhanesh *, Gaelle Duthler , Kang Li
College of Communication and Media Sciences, Zayed University, United Arab Emirates
A R T I C L E I N F O
A B S T R A C T
Keywords:
Engagement
Social media
Public relations
Organization-generated content
Visual
Visual social semiotics
The ubiquity of social media platforms that increasingly foreground visuals over text has led to a rise in
organization-generated visual content. This study addresses an underexamined question about this phenomenon:
which characteristics of organization-generated visual content are associated with higher levels of public
engagement in social media? Engagement is conceptualized as indicators of first level engagement such as likes
and comments that represent affiliation with and support for the organization. Employing a visual social semiotic
framework, a randomly selected sample of visuals posted on Instagram and Facebook by four leading airport
brands in 2019 (N = 400) was coded for representational, interactive, and compositional meanings. Findings
revealed that across platforms narrativity of images, and interactive features of distance and point of view
enhanced engagement, while the compositional feature of framing increased engagement on Instagram. Impli­
cations of the findings for effective organization-generated visual content on social media are discussed.
1. Introduction
Every second, 1046 photographs are uploaded on Instagram and
87,926 videos are viewed on YouTube (Internet live stats, 2021). The
massive uptake of social media platforms that tend to foreground visual
imagery over text has enhanced the production and consumption of
visuals over social media, leading to the visual acculturation of social
media users (Dhanesh, 2017a, Dhanesh & Rahman, 2021; Edwards,
2018). 91% of consumers now prefer visual over text-based media
(Forbes, 2018) and in an age of rapid information consumption, content
with images generate far more user engagement than content without
images (Li & Xie, 2020; Brubaker & Wilson, 2018).
Subsequently, organizations have been employing visuals in their
social media communication to strengthen engagement with their
publics, because social media engagement metrics signal publics’ affil­
iation and identification with organizations, trigger further online in­
teractions in their peer networks, could lead to positive attitudes
towards and stronger relationships with organizations, and increase
purchase intentions (Argyris, Wang, Kim, & Yin, 2020; Brubaker &
Wilson, 2018; Dhanesh & Rahman, 2021; Lim & Childs, 2020, Valentini,
Romenti, Murtarelli, & Pizzetti, 2018). Despite the surge in the con­
sumption and production of visual content on social media, there has
been limited research on the role of visuals to enhance engagement with
organization-generated social media content. This scarce research has
examined how a few aspects of visual content could drive engagement
such as visual appeals (Dolan, Conduit, Frethey-Bentham, Fahy, &
Goodman, 2019; Rietveld, Van Dolen, Mazloom, & Worring, 2020), vi­
sual descriptions (Hwong, Oliver, Van Kranendonk, Sammut, &
Seroussi, 2017), narrativity of visuals (Romney & Johnson, 2020), the
gaze of the subject, and product salience (Valentini et al., 2018). Studies
have also examined genre-specific engagement enhancers with info­
graphics (Amit-Danhi & Shifman, 2020), news articles (Berger & Milk­
man, 2012), and news videos (Ksiazek, Peer, & Lessard, 2016). Research
needs to examine multiple aspects of visuals that could enhance
engagement with the important but under-examined genre of
organization-generated content. As a genre, organization-generated vi­
sual content, defined as organization-initiated visual communication on
the organization’s own social media accounts, is important to study as it
is different from advertisements in that coping mechanisms are not
triggered as in the case of advertisements, and they offer more diversity
in content unlike advertisements that tend to repeat (Rietveld et al.,
2020).
The concept of engagement is particularly pertinent within public
relations practice and research as organizations increasingly employ
* Correspondence to: College of Communication and Media Sciences, Zayed University, PO Box 19282, Dubai, United Arab Emirates.
E-mail address: ganga.dhanesh@zu.ac.ae (G. Dhanesh).
https://doi.org/10.1016/j.pubrev.2022.102174
Received 25 June 2021; Received in revised form 9 February 2022; Accepted 27 February 2022
Available online 14 March 2022
0363-8111/© 2022 Elsevier Inc. All rights reserved.
G. Dhanesh et al.
Public Relations Review 48 (2022) 102174
social media in their communication mix to reach, connect, and build
relationships with publics (Jiang, Luo, & Kulemeka, 2016; Men, O’Neil,
& Ewing, 2020; Smith & Gallicano, 2015). For over a decade, public
relations researchers have examined theoretical conceptualizations of
public/stakeholder engagement (Taylor & Kent, 2014; Taylor, Vasquez,
& Doorley, 2003), employee engagement (Welch, 2011; Verčič & Ćorić,
2018), and most importantly, public engagement over social media
(Avidar, Ariel, Malka, & Levy, 2015; Bowen, 2013; DiStatso, 2012; Jiang
et al., 2016; Lovari & Parisi, 2015; Men & Tsai, 2013, 2014, 2015; Smith
& Gallicano, 2015; Wang & Yang, 2020; Wigley & Lewis, 2012; Yang &
Kang, 2009). Yet only a handful of studies has examined the use of vi­
suals in engendering public engagement (e.g., Brubaker & Wilson, 2018;
Fraustino, Lee, Lee, & Ahn, 2018; Valentini et al., 2018). According to
Pressgrove, Janoske, and Haught (2018) research on the visual in public
relations “only scratches the surface of what the intersection of public
relations and visual communication entails” and called for more
research on the use of visuals in public relations (pp. 318–319).
Since visual content is different from textual forms, it needs
specialized approaches for analysis (Bock, 2020). Accordingly, similar to
the approach employed by Valentini et al. (2018), this study drew on
Kress and Van Leeuwen’s (1996) visual social semiotic approach that
examines representational, interactive, and compositional meanings of
visuals, to examine the characteristics of visual content generated by
organizations that are associated with higher levels of public engage­
ment on social media. More specifically, we conducted a content anal­
ysis of Facebook and Instagram pages of four international airports to
examine how they employed visuals in their posts to engage publics. We
chose to focus on two prominent engagement metrics – likes and com­
ments – on Facebook and Instagram because in corporate social media
communication, these metrics are considered important measures of
evaluation as users’ communicative behaviors reflect reactions to
corporate message strategies on social media (Linders, 2012; Lovari &
Parisi, 2015). We chose Facebook and Instagram because they are two of
the most widely used platforms in organizational social media
communication (Statista, 2021).
This study enhances the literature on organizational visual commu­
nication and public engagement with organizations over social media by
examining a comprehensive set of characteristics of visuals that could
enhance engagement in the important but under-explored genre of
organization-generated visual content. These are important contribu­
tions as most extant literature has only considered the effects of a limited
number of dimensions of visual content in certain genres (Bock, 2020).
Theoretically, findings add multi-dimensional insights into
organization-generated visual content that enhances public engage­
ment, thus enhancing genre-specific insights into drivers of visual digital
engagement. Practically, findings can help organizational practitioners
to adjust their visual content offerings effectively to connect and engage
with publics on social media.
et al., 2018). This study has adopted the term public engagement as it is
one of the most commonly used terms in public relations research to
refer to engagement with various publics over social media, and because
it includes multiple stakeholders who have in common their engagement
with the organization’s social media accounts.
Within public relations scholarship, there are two major strands of
research on public engagement. One strand conceptualizes public
engagement as communicative interaction using first-level engagement
metrics of social media usage such as clicks, likes, views, shares, com­
ments, tweets, reviews, recommendations and other user-generated
content (Agostino, 2013; Brubaker & Wilson, 2018; Jiang et al., 2016;
Kim & Yang, 2017; Men & Tsai, 2013; Men, Tsai, Chen, & Ji, 2018).
According to Smith (2017), a hierarchy of social media metrics ranges
from exposure, engagement, and influence, to impact and advocacy. In
the second strand of research, scholars have stepped beyond equating
engagement with communicative interaction and social media usage
and have considered cognitive, affective, and behavioral dimensions of
public engagement over social media that could foster relationships and
identification with the organization (Dhanesh, 2017b; Smith & Galli­
cano, 2015; Yang & Kang, 2009). Although theoretical explications of
engagement have expanded to include multiple dimensions of engage­
ment, most empirical research on public engagement with organizations
over social media has examined communicative interaction online,
measured by first-level engagement metrics such as likes, comments,
retweets and shares. Accordingly, this study adopted Men and Tsai’s
(2014) definition of public engagement as “a behavioral construct with
hierarchical activity levels, from passive message consumption to active
two-way conversation, participation, and online recommendation” (p.
419).
Empirical research on public engagement, particularly within
corporate public relations, includes work that examines the conceptu­
alization of public engagement on social media (e.g., Jiang et al., 2016;
Men & Tsai, 2013), communication strategies employed in organiza­
tional social media content such as dialogic principles that predict public
engagement (e.g., Men et al., 2018; Watkins, 2017), and the effect of
public engagement on organizational outcomes such as perceptions of
corporate authenticity, organizational transparency, organizational
identification and attachment, positive electronic word-of-mouth
communication,
sense
of
conversational
exchange,
and
organization-public relationships (Men & Tsai, 2013; Wang, Ki, & Kim,
2017).
However, although social media platforms tend to foreground visual
imagery over text, which has led to the visual acculturation of social
media users (Dhanesh, 2017a; Edwards, 2018) and content with images
generate higher user engagement than content without images (Bru­
baker & Wilson, 2018; Li & Xie, 2020) only limited research has
examined the influence of visuals in engendering public engagement
with organizations over social media, reviewed next.
2. Background
2.2. Visuals and engagement with organization-generated content
2.1. Public engagement with organizations over social media
Research that has examined the effect of organization-generated
visuals on engagement over social media has found positive effects of
visual appeals (Dolan et al., 2019; Rietveld et al., 2020), visual de­
scriptions (Hwong et al., 2017), visual complexity (Lee, Hur, & Watkins,
2018), visual point of view (Hur et al., 2020; Zappavigna, 2016), and
narrativity of visuals (Romney & Johnson, 2020) on social media
engagement metrics such as views, likes, retweets, comments, and
shares across Twitter, Instagram and Facebook. Although not exactly
organization-generated content, visual content in influencer marketing
has also been found to generate followers’ engagement with influencer’s
and the brand’s posts (Argyris et al., 2020). Examining user-generated
content on brands, Li and Xie (2020) found that mere presence effect
of image content, image characteristics such as high quality profes­
sionally shot photos, and image-text fit enhanced user engagement on
Instagram and Twitter.
The topic of engagement with organizations over social media goes
by various terms across fields such as marketing, advertising, consumer
research, strategic communication, public relations, and information
and communication technology. While terms such as social media
engagement, digital engagement, and dialogic engagement are typically
used to refer to engagement between organizations and their publics in
general, terms such as public engagement, consumer brand engagement,
user engagement, civic engagement, community engagement, and
employee engagement highlight engagement from the perspective of
specific publics and each has its own body of knowledge (Brubaker &
Wilson, 2018; Gómez, Lopez & Molina, 2019; Hollebeek, Glynn, &
Brodie, 2014; Hollebeek & Macky, 2019; Jiang et al., 2016; Lovari &
Parisi, 2015; Smith & Gallicano, 2015; Taylor & Kent, 2014; Valentini
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Public Relations Review 48 (2022) 102174
Within public relations research, only a handful of studies has
examined the effect of visuals on public engagement over social media.
Kim and Yang (2017) content analyzed Facebook posts of 20 companies
and found that visual features of messages led to more likes in an
affectively driven process, while it led to more shares driven by a
combination of affect and cognition. Brubaker and Wilson (2018)
examined 1393 Facebook posts of the top 100 brands and found that a
combination of texts and visuals work best in engendering user
engagement. Valentini et al. (2018) conducted an experiment and found
that direct gaze and high product salience of visuals positively affected
digital visual engagement. Through data mining and computer-assisted
sentiment analysis of 33,379 posts from 106 Standard & Poor 500
companies’ Facebook accounts, Ji, Chen, Tao, and Cathy Li (2019)
found a positive effect of the functional trait of vividness on public
engagement. Finally, Guidry, Jin, Orr, Messner, and Meganck (2017)
found that incorporating visual imagery in health organizations’ social
media posts can affect social media engagement. While these studies
have offered valuable insights into the role of visuals in engendering
engagement over social media with organization generated content,
most of these studies have focused on only one or a few characteristics of
visuals, and have not examined multiple variables that could predict
public engagement, which has been highlighted as a limitation in visual
studies research (Bock, 2020). Since visual content is distinct from
textual and needs to be studied with specific approaches, this study
examined a wider set of characteristics of visuals following Kress and
Van Leeuwen’s (1996) approach to visual social semiotics.
background as a context, can lead to higher levels of audience trans­
portation and self-brand connection than exposure to images with no
narrative elements in Instagram brand communication (Lim & Childs,
2020). Multiple narrative elements – actors, plots, and settings – were
employed in Twitter and Facebook images employed by U.S. presiden­
tial candidates to deliver narratives of credibility (Page & Duffy, 2018).
Visual content that employs narratives also triggered sharing behavior
among users. For instance, Instagram messages from sports networks
(CBS, ESPN, Fox, NBC) that contained narrative images generated
higher user engagement manifested as likes and comments than those
that contained conceptual images (Romney & Johnson, 2020). Simi­
larly, tweets that contained visual elements were found to have higher
narrativity score, and were liked and shared more than those without
(Boscarino, 2020). Hence, we posited the following hypothesis.
H1:. Content with narrative images will generate more public
engagement than those without narrative images.
2.3.2. Interactive meaning
Interactive meaning refers to how images can interact with viewers
and implies a range of attitudes viewers could adopt towards subjects in
visuals. It is examined through (a) contact or the usage of direct or in­
direct gaze of the subject; (b) the social distance between subject and
viewer; and (c) points of view or angles of shots (Jewitt & Oyama, 2001;
Kress & Van Leeuwen, 1996).
Contact refers to the gaze of the main subject directed at the viewer,
or how it establishes contact with the viewer. Subject/s could engage
viewers through direct or indirect gaze. Direct gaze indicates how
people in the picture can demand something from viewers such as
respect or pity, which can be further strengthened with gestures. An
indirect gaze, on the other hand, does not invite direct engagement with
viewers; instead, it indicates that the subjects are merely offering in­
formation to viewers, not necessarily demanding something (Jewitt &
Oyama, 2001; Kress & Van Leeuwen, 1996).
A substantial body of research on gaze, particularly within the field
of psychology, has revealed that direct gaze can lead to higher social
perceptions of trustworthiness (Bayliss & Tipper, 2006; Willis, Palermo,
& Burke, 2011) attractiveness (Kampe, Frith, Dolan, & Frith, 2001;
Mason, Tatkow, & Macrae, 2005), likability (Mason et al., 2005), and
increased perception of approach-oriented emotions such as anger and
joy (Adams & Kleck, 2005). Conversely, indirect or averted gazes are
often associated with adverse outcomes such as negative judgments of
trustworthiness (Willis et al., 2011) and perception of
avoidance-oriented emotions such as fear and sadness (Adams & Kleck,
2005). Further, gaze shifts indicate attentional engagement or disen­
gagement, with direct gaze generating stronger engagement between
subject and viewer, and indirect gaze causing disengagement (Jewitt &
Oyama, 2001; Kress & Van Leeuwen, 1996; Mason et al., 2005).
Limited research on the effect of gaze in brand communication has
also revealed positive effects of direct gaze. For instance, the effect of
facial expressions of dogs on product packaging on product evaluation is
moderated by direct gaze (Park & Kim, 2020), and the direct gaze of
celebrities on social networking sites can enhance self-celebrity
connection and behavioral intentions (Ilicic & Brennan, 2020). More
relevant to this study, direct gaze in branded Instagram images can lead
to higher digital visual engagement and purchase intentions (Valentini
et al., 2018). The above body of work led us to posit the following.
2.3. Visual social semiotics
According to Kress and Van Leeuwen (1996), visuals perform three
kinds of semiotic work, referred to as metafunctions – representational,
interactive, and compositional. Explications of each of these meta­
functions and empirical research linking it to public engagement drawn
from the fields of marketing, advertising, branding, public relations, and
strategic communication, and hypotheses and research questions are
discussed in the following paragraphs.
2.3.1. Representational meaning – narrative
Representational meaning of an image is conveyed through the
participants depicted in visuals. Two kinds of visual syntactic patterns
relate participants meaningfully to each other – narrative and concep­
tual. While narrative representations refer to how people, places and
things are related to each other in terms of actions or happenings, or the
unfolding of events as in a story, conceptual representations refer to how
images represent participants as being something, belonging to a class or
category; not necessarily acting or doing something. In this study, we
focused on narrative representations because in public relations
research, the value of storytelling as a strategic tool to strengthen or­
ganizations’ engagement and relationships with publics has been
emphasized (Gill, 2015; Kent, 2015). However, most of the work within
public relations has focused on storytelling through text and not through
visual content.
Fisher’s (1989) narrative paradigm underscores the importance of
storytelling to enable meaningful communication and understanding in
human societies through the use of narrative rationality wherein formal
features of a story are presented as a sequence of thought or action.
According to visual social semiotics (Jewitt & Oyama, 2001; Kress & Van
Leeuwen, 1996), a narrative representation typically has an actor and
the recipient of that action, referred to as a goal. Narrative images will
include some indication of action that connects the participants. When
an image includes both an actor and a goal the picture is said to be
transactive, representing a transaction or an exchange between two
parties. However, narrative pictures can also be non-transactive wherein
the action is not directed at a specific entity. This study considered both
transactive and non-transactive narrative representations.
Narrativity in visuals, measured by implied motion and the
H2:. Visuals that employ subjects with direct gaze will have higher
public engagement than visuals that employ subjects with indirect or
averted gaze.
Another way to establish interaction is through the distance depicted
between subjects and viewers, which is also reflective of norms in social
relations that affect the distance maintained by individuals in everyday
interaction (Jewitt & Oyama, 2001; Kress & Van Leeuwen, 1996). In
face-to-face interactions, individuals and groups dynamically adjust
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Public Relations Review 48 (2022) 102174
distance between them and others to regulate the quality of the ex­
change on dimensions such as approach-avoidance and intimacy, a field
of study referred to as proxemics (Hall, 1966). Individuals manage space
in somewhat concentric circles – intimate, personal, social, and public –
with reducing intimacy levels as circles widen. While social contact
between acquaintances typically occurs within the social space, the
personal and intimate distances are for close contact with family and
friends. The idea of para-proxemics encapsulates the relationship be­
tween subjects and viewers through mediated body language corre­
sponding to everyday social interaction (Meyrowitz, 1986). The
proximity of a subject to the camera can elicit a response from the
viewer, similar to the distance experienced in face-to-face interactions.
For instance, a close-up shot brings subjects and viewers in close contact
as though reflecting intimate social relations. A medium shot implies a
social relationship, while a long shot implies an impersonal relationship.
Effects of proxemics such as higher viewer engagement and atten­
tional involvement have been observed not only in face-to-face but also
in digital contexts, particularly in virtual 3D environments (Bailenson,
Blascovich, Beall, & Loomis, 2001; Cafaro, Ravenet, Ochs, Vilhjálmsson,
& Pelachaud, 2016; Petras, ten Oever, & Jansma, 2016) and in the
interaction between selfies and viewers (Bruno, Uccelli, Pisu, Belluardo,
& De Stefani, 2020; Holiday, Loof, Cummins, & McCord, 2019). For
instance, Petras et al. (2016) found that in a virtual shooting task,
shooting a subject at close quarters created more moral engagement
than shooting one who was far more distant. Thus, we posited the
following:
Discontinuity or continuity implying belongingness or separateness can
be imbued with more meaning through the context (Jewitt & Oyama,
2001; Kress & Van Leeuwen, 1996). While a number of studies on visual
framing have analyzed thematic frames used in framing (Bock, 2020),
limited work has been conducted on the effects of framing as a
compositional aspect of visuals. Hence, we posed a research question.
H3:. Visuals that employ close up shots of the subject will have higher
public engagement than visuals that employ medium or long shots.
H4:. Visuals that employ high salience will have higher user engage­
ment than visuals with low salience.
RQ 2:. Which type of framing – connection or disconnection – in vi­
suals will have higher user engagement?
According to Kress and Van Leeuwen (1996), salience indicates that
some visual elements in the picture can be made more prominent than
others. This can be achieved through size, color or tonal contrasts.
Salience is an important feature of composition as high product salience
can increase brand awareness and facilitate brand recall (Alba & Chat­
topadhyay, 1986) and affect user engagement (Valentini et al., 2018).
Research in visual attention and decision-making highlight the link
between visual saliency and attention fixation (Itti & Koch, 2000; Par­
khurst, Law, & Niebur, 2002). In brand research on in-store consumer
behavior, brand placement prominence and visual saliency have been
found to affect brand memory, brand attitude, and consumer choices
(Alba & Chattopadhyay, 1986; Milosavljevic, Navalpakkam, Koch, &
Rangel, 2012; Van Reijmersdal, 2009). On webpages too, visual sa­
liency, created particularly through the use of color and contrast, can
affect user emotions (Silvennoinen & Jokinen, 2016) and visual primes
on webpages can affect changes in choice for experts and novices
(Mandel & Johnson, 2002). Hence, we proposed the following:
Interaction can also be established through point of view, which
refers to how subjects are depicted from above, below or eye level.
Typically, while a low angle suggests power over the viewer, eye-level
indicates equality, and high angle implies power of the viewer (Jewitt
& Oyama, 2001; Kress & Van Leeuwen, 1996). Studies that have
examined point of view in visuals tend to be descriptive examining the
depiction of power relations through camera angles (Boulton, 2007;
Bruno et al., 2020; Sedgewick, Flath, & Elias, 2017). For instance, in
print ads for hip-hop clothing depicting child models, the camera angles
tended to be eye level, calling for equal power relations with the
intended audience of affluent parents (Boulton, 2007). Studies on selfies
have also examined camera angle and the power relations it implies.
Sedgewick et al. (2017) content analyzed the use of camera angles in
557 selfies on Tinder, and found that while men used mostly low angles
indicating power over the viewer, women used high angles indicating
less power. Bruno et al. (2020) got similar findings on examining selfies
wherein men tended to use low camera angles while women preferred
eye level or high camera angles. However, these studies are descriptive
and did not examine the relationship between point of view and user
engagement. Hence, we proposed a research question:
3. Method
The research was conducted using a quantitative content analysis to
quantify the presence and frequency of occurrence of the variables in
Instagram and Facebook visual content. The main method employed
was a visual semiotic approach-based content analysis (Bell, 2001) of
Facebook and Instagram images posted by four airport brands.
We chose airport brands because corporate social media communi­
cation of airport brands offers a productive test case for examining user
engagement with brand generated visual content. Airports provide im­
ages of a destination to visitors, exhibit the salient characteristics of the
destination, become the ambassador of the destination, affect visitors’
first and last impressions of the host city, and provide spaces of spec­
tatorship of aircraft (Adey, 2007; Nghieˆm-Phu & Suter, 2018; Watta­
nacharoensil, Schuckert, Graham, & Dean, 2017). Given that travelers
have a greater choice of airports and air services, airports need to focus
on sharpening their marketing strategies. However, most studies on
brand management for airports have focused on customer perspectives,
such as examining how passengers co-create identity through
user-generated Instagram images (Blackwood, 2019), and online re­
views of passengers to ascertain the airport experience and perceptions
of attributes of airports (Nghieˆm-Phú & Suter, 2018; Wattanacharoensil
et al., 2017). Despite the importance of airport branding strategies and
the importance of social media in the brand communication mix, scarce
research has focused on the characteristics of visuals posted by airport
brands that could enhance user engagement. This study sought to fill
that gap by identifying the characteristics of engaging social media vi­
sual content of airport brands.
RQ 1:. Which point of view – high, low, equal – in visuals will generate
higher public engagement?
2.3.3. Compositional meaning
Compositional meaning refers to how individual aspects of repre­
sentation and interaction are brought together to create the whole that
can be recognized as a specific kind of communicative output such as an
advertisement or a film. This includes conventions of composition such
as (a) framing various visual elements as connected or disconnected
from each other; and (b) the prominence or salience of the subject
(Jewitt & Oyama, 2001; Kress & Van Leeuwen, 1996).
Framing refers to how various elements of a visual image can be
given separate identities or shown as belonging together through the use
of lines, empty spaces, or contrasts of color or form. These elements can
be used harmoniously to create a sense of connection among the various
elements or used to create contrasts, divisions and disconnections.
3.1. Sample
The sample consisted of 50 photos on Instagram and 50 photos on
Facebook for four airports: DXB (Dubai International), AMS (Amsterdam
Schiphol), LHR (London Heathrow), and SIN (Singapore Changi) for a
total of 400 photos. These airports were chosen as they are some of the
busiest airports in Europe and Asia (2019 Airport Traffic Report), as well
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as serve as transit hubs connecting various parts of the world. The
sample of social media posts was selected by randomly choosing 50
dates from January 1, 2019 to December 31, 2019. The sample size is
above 25% of the whole population of 1892 image posts. The sampling
error at 95% level of confidence is 4.38%. We used simple random
sampling because probability samples are more appropriate in content
analysis to enable statistical inference, and simple random sampling is
one of the recommended probability sampling methods (Riffe, Lacy,
Watson, & Fico, 2019). We used random sampling also because as part of
the larger study we needed to check how frequently airports used images
with these characteristics.
Once the dates were chosen, the links to the Instagram post and the
Facebook post were entered into an Excel sheet to make sure that re­
searchers would be coding the same post. In case there were no photos
posted for the selected date, the researcher selected the photo from the
day after. If that photo was already selected to be in the sample, the
researchers selected the next available photo that was not included in
the sample.
The unit of analysis was the post for the selected date. The photo was
analyzed as well as the source, the brand, the number of views, likes,
hashtags, mentions, and comments. In case there were two photos
posted the same day, the first one was chosen. Comments were noted but
not analyzed. Thus, a total of 400 posts consisting of the photo and the
engagement data were analyzed.
Based on the discussions, the coding instrument was revised and
improved.
Pilot Study 2 aimed to test the revised coding instrument as well as
train the coders. The sample of this pilot study consisted of 50 random
image posts of the selected brands, which represented 10% of the final
sample size. These 50 posts did not duplicate with the images in the final
sample. The same three coders from Pilot Study 1 participated in this
training and worked independently while coding. After coding, the
coding of each image was reviewed and discussed. Each pair of coders
reached above 90% satisfactory agreement on all variables.
The coding of the final sample started after Pilot Study 2. The three
trained coders coded the final sample independently. Each post was
coded by two coders. Scott’s Pi was used for testing the reliability of the
variables with this final sample. Scott’s Pi intercoder reliability co­
efficients of all the variables ranged from .79 to 1.00, exceeding the
accepted threshold of .70. Coders discussed the inconsistent codes and
revised coding after reaching agreement. The agreed dataset was used
for the data analysis.
4. Results
Since the values of user engagement (i.e., numbers of likes and
comments) were highly skewed, those values were log-transformed to
normalize the distributions for the analysis (Larose & Larose, 2014). The
descriptive raw values (untransformed) of user engagement are sum­
marized in Table 2. As seen in Table 2, likes and comments are higher on
Instagram when compared to Facebook for all brands, although the
number of followers is higher on Facebook than Instagram.
3.2. Procedures
A coding sheet (see Table 1) was developed for the researchers to
measure the independent and dependent variables based on categories
suggested by Bell (2001) for gaze and social distance, and Jewitt and
Oyama (2001) for narrative structures, point of view, framing, and
salience. Before the main study, two pilot studies were conducted for the
purpose of improving the coding instrument and training coders.
Pilot Study 1 tested the coding instrument in order to clarify any
disagreement. In this pilot study, we used 20 DXB Instagram posts as our
sample that were not included in our final sample. Three coders, the
researchers, were trained on how to code posts by using the coding in­
strument and coded the 20 posts independently. To improve the level of
agreement among the coders, each post was then discussed by the three
coders until over 80–90% agreement was achieved across the variables.
4.1. Representational enhancers of public engagement
H1 predicted that visual content with narrative images will generate
more user engagement than those without narrative images. The results
of T-tests showed that on Instagram, the narrative images (M = 3.33, SD
= 0.31) generated significantly higher numbers of likes than the nonnarrative images (M = 3.22, SD = 0.27), t (198) = 2.03, p < .05. However, there was no significant difference between the comments generated by narrative images (M = 1.34, SD = 0.38) and by nonnarrative images (M = 1.30, SD = 0.38), t (198) = 0.59, p = .56. On Facebook, the results showed that narrative images (M = 2.26, SD = 0.73) generated significantly higher numbers of likes than the nonnarrative images (M = 1.90, SD = 0.53), t (198) = 2.23, p < .05. Narrative images (M = 1.23, SD = 0.72) also led to more comments than non-narrative images (M = 0.87, SD = 0.77), t (198) = 2.20, p < .05. Therefore, H1 was partially supported by Instagram data, and fully supported by Facebook data. Table 1 Coding and Measurement of Independent and Dependent Variables. Variable Operationalization Social Media Engagement Narrative Number of likes Number of comments 1 = Narrative: Main action and goal present/Main action present 2 = Non-narrative: Main action absent 1 = Indirect gaze: Main character looks away from the viewer 2 = Direct gaze: Main character looks at the viewer directly 3 = NA (visual does not include people) 1 = Close up shot: intimate and close personal distance 2 = Medium shot: far personal distance 3 = Long shot: close social distance, far social distance, public distance 1 = Low angle 2 = Eye-level 3 = High angle 1 = Connection through similarities and rhymes of color and form; through vectors that connect elements; absence of empty space between elements 2 = Disconnection through contrasts of color or form; through framelines, and empty space between elements 1 = High salience (main product/character is prominent through use of size, color, or tonal contrasts) 2 = Low salience (no main product/character is prominent through use of size, color, or tonal contrasts; or when it is a group with no main subject) Contact (gaze) Social Distance Point of View Framing Salience Table 2 Social Media Posts by Brand. Likes 5 Brand N Dubai International Instagram Facebook Singapore Changi Instagram Facebook London Heathrow Instagram Facebook Amsterdam Schiphol Instagram Facebook 100 No. of followers (as of 03/2020) Comments M SD M SD 965 1612 12 16 1736 194 2625 4603 647 1263 1957 456 2475 1897 894 1663 13 11 48 52 44 34 13 19 60 51 67 46 50 50 100 50 50 100 316K 2.35M 50 50 100 289K 445K 2257 268 1272 1858 337 877 38 30 81 50 40 160 50 50 72K 525K 1898 645 714 494 25 137 22 211 345K 4.6M G. Dhanesh et al. Public Relations Review 48 (2022) 102174 4.2. Interactive enhancers of public engagement numbers of likes generated by high angle and eye-level points of view. As for comments, low angle only generated significantly more comments than high angle points of view. No significant differences were found between the numbers of comments generated by low angle and eye-level points of view, as well as between the comments generated by high angle and eye-level points of view. H2 predicted that visuals that employed subjects with direct gaze would have higher levels of user engagement than visuals that employed subjects with indirect/averted gaze. The results of T-tests showed that on Instagram, visuals that employed subjects with direct gazes (M = 3.29, SD = 0.27) did not generate significantly more numbers of likes than the visuals with indirect gazes (M = 3.18, SD = 0.18), t (65) = 1.53, p = .13. The visuals with direct gazes (M = 1.36, SD = 0.39) also did not generate significantly more comments than visuals with indirect gazes (M = 1.22, SD = 0.31), t (65) = 1.34, p = .19. Similarly, on Facebook, gazes (direct vs. indirect gazes) did not show any significant effects on user engagement in terms of likes (direct gaze: M = 2.13, SD = 0.72; indirect gaze: M = 2.31, SD = 0.76, t (76) = − 0.92, p = .36) and comments (direct gaze: M = 1.22, SD = 0.83; indirect gaze: M = 1.23, SD = 0.65, t (76) = − 0.07, p = .94). Therefore, the data were not consistent with H2. H3 had predicted that visuals that employed close up/personal shots of the subject would have higher user engagement than visuals that employed medium/social or long/public shots. The results of One-Way ANOVA with Post Hoc tests showed that on Instagram, the three types of shots generated different likes, F (2, 197) = 4.01, p < .05. Among the three types, long/public shots (M = 3.34, SD = 0.31) led to more likes than medium/social shots (M = 3.17, SD = 0.27), while there were no significant results found between the other types of shots. The shot types also did not generate different numbers of comments: close-up/personal shots (M = 1.33, SD = 0.37), medium/social shots (M = 1.20, SD = 0.38), long/public shots (M = 1.36, SD = 0.38), F (2, 197) = 2.10, p = .13. The data from Facebook showed significant results about the effects of three shot types on both likes (close-up shots: M = 1.93, SD = 0.63; medium shots: M = 2.19, SD = 0.64, long shots: M = 2.30, SD = 0.76, F (2, 197) = 3.68, p < .05) and comments (close-up shots: M = 0.90, SD = 0.51; medium shots: M = 1.24, SD = 0.79, long shots: M = 1.25, SD = 0.76, F (2, 197) = 3.18, p < .05). The results of Post Hoc tests showed that long/public shots led both more likes and more comments than close-up/personal shots, while there were no significant differences between the user engagement generated by medium/social and long/ public shots, as well as by close-up/personal and medium/social shots. Therefore, H3 was rejected by the data. However, significant results were found for long shots. RQ1 had asked which point of view would generate higher user engagement. The results of One-Way ANOVA with Post Hoc tests showed that on Instagram, the three types of points of views generated significantly different likes: low angle (M = 3.43, SD = 0.30), eye-level (M = 3.33, SD = 0.28), high angle (M = 3.21, SD = 0.32), F (2, 197) = 6.63, p < .01, and significantly different comments (low angle (M = 1.51, SD = 0.41), eye-level (M = 1.33, SD = 0.37), high angle (M = 1.25, SD = 0.36)), F (2, 197) = 5.46, p < .01. The Post Hoc tests showed that on Instagram low angle generated significantly more likes than high angle. No significant differences were found between the numbers of likes generated by low angle and eye-level points of view, as well as between the likes generated by high angle and eye-level points of view. As for the comments, low angle generated significantly more comments than both high and eye-level points of view, while no significant dif­ ference between the numbers of comments generated by high angle and eye-level points of view. The results of Facebook data also showed the three points of view led to significantly different user engagement on Facebook in terms of likes (low angle: M = 2.61, SD = 0.57; eye-level: M = 2.20, SD = 0.74, high angle: M = 2.08, SD = 0.68, F (2, 197) = 4.02, p < .05) and comments (low angle: M = 1.54, SD = 0.70; eye-level: M = 1.18, SD = 0.75, high angle: M = 1.04, SD = 0.66, F (2, 197) = 3.41, p < .05). Slightly different from the results of Instagram data, the Post Hoc tests showed that low angle generated significantly more likes than high angle and eye-level points of view, while no significant difference was found between the 4.3. Compositional enhancers of public engagement RQ2 had asked which type of framing (connection vs. disconnection) would have higher user engagement. The results of T-tests showed that, on Instagram, framing of connection (M = 3.36, SD = 0.32) generated significantly more numbers of likes than the framing of disconnection (M = 3.26, SD = 0.28), t (198) = 2.29, p < .05. The framing of connection (M = 1.40, SD = 0.41) also significantly generated more comments than disconnection (M = 1.27, SD = 0.34), t (198) = 2.59, p < .05. However, on Facebook, no significant results were found. The images employed framing of connection (M = 2.14, SD = 0.74) did not generate more likes than images framed with disconnection (M = 2.31, SD = 0.69), t (198) = − 1.71, p = .09. The framing of connection (M = 1.11, SD = 0.74) also did not lead to more comments than the framing of disconnection (M = 1.26, SD = 0.72), t (198) = − 1.46, p = .15. H4 predicted that visuals that employed high salience would have higher user engagement than those with low salience. No significant results were found regarding this hypothesis. On Instagram, high salience (M = 3.30, SD = 0.31) did not lead to more likes than low (M = 3.37, SD = 0.27), t (198) = − 1.25, p = .21; and there were also no significant differences between the effects of high (M = 1.32, SD = 0.38) and low salience (M = 1.43, SD = 0.35) on comments, t (198) = − 1.67, p = .10. On Facebook, salience (high vs. low) did not show any significant effects on user engagement in terms of likes (high salience: M = 2.21, SD = 0.71; low salience: M = 2.22, SD = 0.79, t (198) = − 0.07, p = .94) and comments (high salience: M = 1.18, SD = 0.74; low salience: M = 1.21, SD = 0.75, t (198) = − 0.26, p = .80). Therefore, H4 was rejected by both Instagram and Facebook data. Please see Table 3 for a summary of each variable’s effect size (η2) on user engagement. 5. Discussion Social media with its heavy reliance on visual imagery have provided a platform for organizations to strengthen engagement with their pub­ lics through the use of organization-generated visual content. This study examined which representational, interactive, and compositional char­ acteristics of visual content generated by organizations are associated with higher levels of public engagement on Facebook and Instagram, thus augmenting the scarce literature on the role of visuals in engen­ dering public engagement with organization-generated visual content over social media. One major finding was that narrativity of visuals enhanced public engagement, particularly likes on Instagram and likes and comments on Table 3 Results Summary of Each Variable’s Effect Size (η2) on User Engagement. Instagram Representational Meaning Narrative Interactive Meaning Gaze Distance Point of view Compositional Meaning Framing Salience Note. *p < .05, **p < .01. 6 Facebook Likes Comments Likes Comments .02* .00 .03* .02* .02 .04* .06** .01 .01 .05** .01 .04* .04* .01 .03* .03* .03* .01 .03* .01 .01 .00 .01 .00 G. Dhanesh et al. Public Relations Review 48 (2022) 102174 Facebook. This finding augments emergent research that narrativity in visuals can generate higher user engagement over Twitter (Boscarino, 2020) and Instagram (Romney & Johnson, 2020). When visuals communicate narrativity, users are more engaged, supporting narrative theorists’ argument that storytelling is a universal language that can connect with audiences not only through text but also visuals. This finding has also offered empirical evidence to support the storytelling perspective within public relations, particularly through the use of vi­ suals in organization-generated content, adding to existence evidence for textual forms of narration (Gill, 2015; Kent, 2015). Consciously choosing visual content that conveys a sense of action will help to garner public engagement. The power of visual narrativity to grab public engagement could be explained by the ability of narrative visuals to generate higher levels of affect, audience transportation and influence self-brand connection (Dhanesh & Rahman, 2021; Kim & Yang, 2017; Lim & Childs, 2020). Another significant aspect of visuals that predicted public engage­ ment was the interactivity of visuals, particularly point of view and distance. This finding is particularly relevant for public relations given that practice and research in public relations tends to foreground twoway interactive communication in verbal contexts. Findings from this study extend the focus on interaction to visuals contexts as well. Inter­ active meaning of visuals indicates how visuals can interact with viewers and grab their attention, prompting them to adopt a certain attitude towards the subjects in the visuals. Findings from this study confirmed that point of view, i.e., the angles through which subjects are depicted, strongly generated likes and comments across Instagram and Facebook, specifically low point of view, indicating power over the viewer. Camera angles can establish power relations between the viewers and the sub­ jects in the visuals and studies have found that the use of camera angles to imply power relations depends on the purpose of communication, whether it is to establish equal power relations to connect child models with affluent parent customers (Boulton, 2007) or to reinforce stereo­ typical power relations in mating contexts (Bruno et al., 2020; Sedge­ wick et al., 2017). Similarly, one probable explanation for our finding could be that organization-generated visual communication of airports employed mostly low camera angles to symbolically suggest power over the viewer, perhaps acknowledging that one of the purposes of organization-generated visual communication of airports is to establish airports as spaces of spectatorship where travelers are enthralled by the viewing of aircraft (Adey, 2007). This finding could also be explained by the nature of the main subjects in the images – planes on runways and in flight, indicating that organizations’ use of camera angles in their visuals could be context dependent. Yet another interactive feature that significantly predicted likes on Instagram and likes and comments on Facebook was social distance, which can regulate feelings of intimacy between the viewer and the subject in the visual. Although closer para-proxemic distances between subjects and viewers has been found to generate higher user engagement in the case of virtual 3D environments (Bailenson et al., 2001; Cafaro et al., 2016; Petras et al., 2016), and selfies (Bruno et al., 2020; Holiday et al., 2019), this finding did not hold up in the case of organization-generated visual communication. Instead, long shots enhanced user engagement. This could be because most of the subjects in the sample were planes, airport buildings, and runways. Panoramic, long shots might have been employed to cater to publics’ expectation of spectatorial experience of airports than medium or close up shots of minutiae, such as a product in a store or food served in an airport café or restaurant. As for the third element of interactive meaning – gaze – although limited research in brand communication has found that direct gaze in branded images can positively affect digital visual engagement and purchase intentions on Instagram (Valentini et al., 2018), this study revealed that direct gaze did not enhance public engagement. This could be because the majority of our sample did not include people, but scenes and objects, and gaze was coded only when the subject was a person. Finally, given the visual information overload on social media, although one would expect organizations to focus on visual composition to stand out in a cluttered sea of images, vying for the scarce attention of publics (Li & Xie, 2020), we found that the compositional aspects of visuals did not generate public engagement, except that framing harmonious connections among various elements in the visuals gener­ ated likes and comments on Instagram. This could be explained by the affordances of Instagram, which foregrounds visual content over textual (Waterloo, Baumgartner, Peter, & Valkenburg, 2018). This comprehensive comparison of various representational, inter­ active and compositional meanings of organization-generated visual content on Instagram and Facebook suggests that among the three meaning making aspects of visuals, narrativity and interactivity, particularly social distance and point of view were most prominent, followed by the compositional aspect of framing harmonious connec­ tions among the elements within the visual. Therefore, we can conclude that organization-generated visual content can significantly engender public engagement over social media. These findings are critical because public engagement can strengthen user-brand affiliation, strengthen social informational environments of peer networks and influence out­ comes such as purchase intentions (Brubaker & Wilson, 2018; Dhanesh & Rahman, 2021; Lim & Childs, 2020; Valentini et al., 2018). As for contribution to building theory, this study suggests that visual social semiotics is a useful framework for examining organizationgenerated visual content and its influence on public engagement. Literature on visual studies has been limited to examining only a few aspects of visuals (Bock, 2020). By employing the theoretical framework of visual social semiotics and examining representational, interactive, and compositional meanings of visuals, this study enhances the body of work in digital visual engagement. The study also augments the emer­ gent body of work in public relations on visual communication (Press­ grove et al., 2018) and offers multiple avenues for future research on visual communication in public relations. This study contributes to expanding understanding of visuals that can generate public engage­ ment with organization-generated content. Finally, this study may also help to advance the growing body of literature on visual communication in the underexamined genre of organization-generated content. The study also has implications for practice, particularly for public relations practitioners and anyone who manages organizations’ public engagement through social media. Findings can encourage practitioners to continue with or start to use visuals in organization-generated con­ tent. Further, insights on the narrativity, interactivity and compositional aspects of visuals in organization-generated content can help practi­ tioners to choose the most effective visuals to generate public engage­ ment as they build relationships with various publics through social media. Visual storytelling creates a connection between the organization and the public on a more personal level by stimulating feelings and emotions. These visuals can help public relations manage the brand’s identity on social media by drawing the public into the narrative through affective, interactive routes. 5.1. Limitations This study is not without its limitations. First, only organizations from one sector was included in the sample. As a result, the findings of this study might not be generalizable to organizations in other in­ dustries. This is particularly true for the findings on interactivity that contrary to existing research found that different types of social distance and points of view engaged publics of airports. Second, the study only considered the role of visuals in influencing public engagement. How­ ever, organization-generated communication is multimodal and the role of visuals, text, and perhaps audio in influencing public engagement simultaneously needs to be examined. This is particularly important as we had noticed in our study that sometimes, a post could have generated high engagement metrics not necessarily because of the picture but because of the accompanying text or caption. Third, the study used content analysis to measure public engagement and could not determine 7 Public Relations Review 48 (2022) 102174 G. Dhanesh et al. the public’s interest in traveling, airports, or airplanes. Using interviews, focus groups, or surveys could gauge people’s experience and provide a clearer understanding of the underlying reasons for their engagement. Finally, the study investigated interactive meaning by analyzing pictures of people as well as planes and airports. The findings need to be contextualized as the pictures of planes and people would require different elements of visual design, such as gaze, angle, and distance. See for instance, work by Durrani (2020) that extended Van Leeuwen’s (2008) work on visual othering and conducted a semiotic examination of how the interactive cues of gaze, camera angle and social distance accorded more power to Iranian male dissidents and female trailblazers in photojournalism in the Time magazine. Agostino, D. (2013). Using social media to engage citizens: a study of Italian municipalities. Public Relations Review, 39, 232–234. Alba, J. W., & Chattopadhyay, A. (1986). Salience effects in brand recall. 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Future research Future research could address some of these limitations and employ a visual social semiotic approach to examine how organizations in other industries employ visuals to generate public engagement. This could contribute to strengthening the body of literature on the genre of organization-generated content and the characteristics of visuals that could influence public engagement across a wider set of industries. Research could also employ experiments to examine the effects of representational, interactive and compositional aspects of organizationgenerated visual content on public engagement. From the perspective of publics, research could examine the motivations of publics to engage with organization-generated visuals. Further, future research could employ yet another significant semiotic system for analyzing composi­ tional meanings, devised by Caple (2013). Finally, research could combine the comprehensive visual social semiotic approach with tex­ tual/linguistic analysis and examine how the influence of multiple modalities of communication could affect public engagement with organization-generated content over social media. CRediT authorship contribution statement Ganga Dhanesh: Funding acquisition, Conceptualization, Data Analysis, Writing. Gaelle Duthler: Data curation, Methodology, Data Analysis, Project administration. Kang Li: Data curation, Methodology, Data Analysis. Funding details This work was supported by Dubai Airports under PO number 41907170. The funding source had no involvement in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the article for publication. Declaration of interest There is no potential conflict of interest as the data was collected from publicly available sources and the funding organization did not have any role to play in the research process across study design, conceptualization, data collection, analysis, and writing. Data availability The data that support the findings of this study are available from the corresponding author upon request. References Adams, R. B., & Kleck, R. E. (2005). Effects of direct and averted gaze on the perception of facially communicated emotion. Emotion, 5(1), 3–11. Adey, P. (2007). ‘May I have your attention’: airport geographies of spectatorship, position, and (im) mobility. Environment and Planning D: Society and Space, 25(3), 515–536. 8 G. Dhanesh et al. Public Relations Review 48 (2022) 102174 Gómez, M., Lopez, C., & Molina, A. (2019). An integrated model of social media brand engagement. Computers in Human Behavior, 96, 196–206. https://doi.org/10.1016/j. chb.2019.01.026 Guidry, J. 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