Initial research on emoji suggests that they fulfill
similar roles as emoticons, although emoji are more
visually complex and may be expected to function
somewhat differently in CMC as a consequence. For
example, [7] found that emoji had a greater effect than
emoticons on reader perceptions of a writer’s
commitment and personal mood. At the same time,
there are important limitations to emoji use, due in part
to the fact that different viewing platforms render
emoji differently. [16] found that people often
disagreed on the sentiment and meaning of the same
visual representation of an emoji, and these
disagreements only increased when the “same” emoji
were compared across platforms.
Research on photographic images typically does
not focus on their conversational functions [e.g., 25,
26]. However, there are some notable exceptions. [28]
examined the use of personal photographs in online
chat. [15] analyzed a community image blog and found
six conversation styles, including image quote and
text-in-picture. [6] studied Radar, a mobile application
that allows users to post personal photographs,
including ‘selfies,’ to a private list of invited friends.
Users of Radar sometimes exploited the chronological
nature of the app to post sequences of images meant to
tell a story. [5] found that images on a messaging
application were woven into the thread of conversation
meaningfully, rather than simply being mentioned.
Another study [10] explored how selfies are
perceived and used in the U.S., U.K., and China
through surveys and interviews. The respondents
reported that selfies often elicited comments and
encouraged conversational partners to send their own
selfies in reply. U.S. respondents also indicated a high
enjoyment of conversational partners ‘playing on’
shared images, especially on Snapchat.
An internet meme is a “particular idea presented as
a written text, image, language ‘move,’ or some other
unit of cultural ‘stuff’” that is taken up and spreads
rapidly [11, p. 202]. Considerable research has been
done on how memes form and spread [e.g., 22, 23], but
there has been less research on how such memes are
used in conversational exchanges. An exception is
[29], which explores CAHOOTS, a chat system that
continuously analyzes participants’ chat and suggests
relevant humorous images and internet memes. In
comparison to random image insertion and plain text
chat, users preferred using CAHOOTS. They felt that
the way the system allowed human and computer to
riff off one another enabled them to express their
unique sense of humor. Another study analyzed how
internet memes were used in the Occupy Wall Street
movement [17]. It found that image memes facilitated
conversation from divergent perspectives and increased
the accessibility of the discourse.
Little research has investigated how videos are
included in ongoing conversational contexts, although
[9] investigated how young girls use video messages to
chat in VideoPal, an asynchronous communication
system designed around the exchange of videos, and
[19] analyzed a religious debate that occurred through
the dyadic exchange of videos on YouTube.
GIFs are also understudied, although what research
has been done is suggestive. The preliminary analysis
of Tumblr posts carried out by [2] found that animated
GIFs typically expressed reactions to previous
propositions, and they expressed more emotion, more
intensely, and were more positive in valence than text.
Similarly, [18] characterized exchanges involving
reaction GIFs and images in a Sherlock fan group on
Tumblr as conversational interaction.
One of the very few papers to consider stickers [13]
suggested that stickers, together with photographs,
videos, and emoji, function to improve the
interpretability of messages and help users express
complex emotions. At the same time, the author noted
(p. 3) that stickers can lend instant messages “an air of
equivocation, allowing the conversation to be shaped
by the different parties as it went along.” This
observation recalls the findings of [16] regarding the
potential ambiguity of emoji.
There is thus considerable evidence that each
graphicon type can function pragmatically in CMC,
although little research has taken a conversational or
discourse approach to graphicon use. Moreover, most
previous studies have analyzed graphicon types
individually, rather than comparing across types. In
this study, we employ a discourse-pragmatic approach
and systematically compare multiple graphicon types
in order to understand how they function in relation to
one another in conversational threads.
Specifically, we address two research questions:
RQ1: How often are different graphicons used in FB
comment threads in groups devoted to
graphical content?
RQ2: How do different graphicons function in FB
comment threads in groups devoted to
graphical content?
3. Methodology
3.1. Data
The use of multiple graphicon types in Facebook
comment threads is a relatively new and as yet not
widespread phenomenon. To locate groups with a rich
concentration of graphicons to analyze for the purpose
of this study, we searched in Facebook for the
keywords (ASCII) Emoticons, Emoji/Smileys,
2186
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