Emoticon Style: Interpreting Differences in Emoticons Across Cultures

Park, Jaram; Barash, Vladimir; Fink, Clay; Cha, Meeyoung

doi:10.1609/icwsm.v7i1.14437

Cited by 50 publications

(14 citation statements)

References 17 publications

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“…Emoticons, or "typographic symbols that appear sideways as resembling facial expressions," (Walther and D'Addario 2001) such as :), have been in use in text-based communication since at least the early 1980s, with numerous studies documenting their prevalence in SMS texts (Tossell et al 2012), blogs (Huffaker and Calvert 2006), and, more recently, Twitter (Park et al 2013). Much research has focused on the role that emoticons can play in complementing traditional text-based computer-mediated communication (CMC).…”

Section: Emoticonsmentioning

confidence: 99%

“Blissfully Happy” or “Ready toFight”: Varying Interpretations of Emoji

Miller

Thebault-Spieker

Chang

et al. 2021

ICWSM

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Emoji are commonly used in modern text communication. However, as graphics with nuanced details, emoji may be open to interpretation. Emoji also render differently on different viewing platforms (e.g., Apple’s iPhone vs. Google’s Nexus phone), potentially leading to communication errors. We explore whether emoji renderings or differences across platforms give rise to diverse interpretations of emoji. Through an online survey, we solicit people’s interpretations of a sample of the most popular emoji characters, each rendered for multiple platforms. Both in terms of sentiment and semantics, we analyze the variance in interpretation of the emoji, quantifying which emoji are most (and least) likely to be misinterpreted. In cases in which participants rated the same emoji rendering, they disagreed on whether the sentiment was positive, neutral, or negative 25% of the time. When considering renderings across platforms, these disagreements only increase. Overall, we find significant potential for miscommunication, both for individual emoji renderings and for different emoji renderings across platforms.

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Section: Emoticonsmentioning

confidence: 99%

“Blissfully Happy” or “Ready toFight”: Varying Interpretations of Emoji

Miller

Thebault-Spieker

Chang

et al. 2021

ICWSM

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“…Some scholars have documented the linguistic style of particular media, in order to better understand how users exploit and expand their communication affordances (e.g., (Hu, Talamadupula, and Kambhampati 2013)) or when and why people might change their linguistic style (Danescu-Niculescu-Mizil et al 2013;Michael and Otterbacher 2014). In contrast, others have studied the correlation between participants' linguistic patterns and their offline demographics and identities (e.g., (Pennacchiotti and Popescu 2011;Fink, Kopecky, and Morawski 2012;Park et al 2013).…”

Section: Discussionmentioning

confidence: 99%

Linguistic Bias in Collaboratively Produced Biographies: Crowdsourcing Social Stereotypes?

Otterbacher

2021

ICWSM

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Language is the primary medium through which stereotypes are conveyed. Even when we avoid using derogatory language, there are many subtle ways in which stereotypes are created and reinforced, and they often go unnoticed. Linguistic bias, the systematic asymmetry in language patterns as a function of the social group of the persons described, may play a key role. We ground our study in the social psychology literature on linguistic biases, and consider two ways in which biases might manifest: through the use of more abstract versus concrete language, and subjective words. We analyze biographies of African American and Caucasian actors at the Internet Movie Database (IMDb), hypothesizing that language patterns vary as a function of race and gender. We find that both attributes are correlated to the use of abstract, subjective language. Theory predicts that we describe people and scenes that are expected, as well as positive aspects of our in-group members, with more abstract language. Indeed, white actors are described with more abstract, subjective language at IMDb, as compared to other social groups. Abstract language is powerful because it implies stability over time; studies have shown that people have better impressions of others described in abstract terms. Therefore, the widespread prevalence of linguistic biases in social media stands to reinforce social stereotypes. Further work should consider the technical and social characteristics of the collaborative writing process that lead to an increase or decrease in linguistic biases.

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“…The smiley became an inspiration for the creation of emoticons varying in both expression and design (Tomic ́et al, 2014). Since their inception, a substantial amount of research has been dedicated to investigating (i) the role of emoticons as socio-emotional providers in messages, among other channels of written communication (for reviews, see Aldunate & González-Ibáñez, 2017;Derks et al, 2008b); (ii) the variety and frequency of emoticon use in mixed-gender communication (e.g., Tossell et al, 2012); and (iii) the adequacy of emoticon comprehension in intercultural communication (e.g., Cheng, 2017;Kavanagh, 2010;Park et al, 2013;Sugimoto & Levin, 2000;Takahashi et al, 2017).…”

Section: Emoticonsmentioning

confidence: 99%

Color Affects Recognition of Emoticon Expressions

2022

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In computer-mediated communication, emoticons are conventionally rendered in yellow. Previous studies demonstrated that colors evoke certain affective meanings, and face color modulates perceived emotion. We investigated whether color variation affects the recognition of emoticon expressions. Japanese participants were presented with emoticons depicting four basic emotions (Happy, Sad, Angry, Surprised) and a Neutral expression, each rendered in eight colors. Four conditions (E1–E4) were employed in the lab-based experiment; E5, with an additional participant sample, was an online replication of the critical E4. In E1, colored emoticons were categorized in a 5AFC task. In E2–E5, stimulus affective meaning was assessed using visual scales with anchors corresponding to each emotion. The conditions varied in stimulus arrays: E2: light gray emoticons; E3: colored circles; E4 and E5: colored emoticons. The affective meaning of Angry and Sad emoticons was found to be stronger when conferred in warm and cool colors, respectively, the pattern highly consistent between E4 and E5. The affective meaning of colored emoticons is regressed to that of achromatic expression counterparts and decontextualized color. The findings provide evidence that affective congruency of the emoticon expression and the color it is rendered in facilitates recognition of the depicted emotion, augmenting the conveyed emotional message.

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Emoticon Style: Interpreting Differences in Emoticons Across Cultures

Cited by 50 publications

References 17 publications

“Blissfully Happy” or “Ready toFight”: Varying Interpretations of Emoji

“Blissfully Happy” or “Ready toFight”: Varying Interpretations of Emoji

Linguistic Bias in Collaboratively Produced Biographies: Crowdsourcing Social Stereotypes?

Color Affects Recognition of Emoticon Expressions

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