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Emoticon Style: Interpreting Differences in Emoticons Across Cultures

TLDR
This paper investigates the semantic, cultural, and social aspects of emoticon usage on Twitter and shows that emoticons are not limited to conveying a specific emotion or used as jokes, but rather are socio-cultural norms, whose meaning can vary depending on the identity of the speaker.
Abstract
Emoticons are a key aspect of text-based communication, and are the equivalent of nonverbal cues to the medium of online chat, forums, and social media like Twitter. As emoticons become more widespread in computer mediated communication, a vocabulary of different symbols with subtle emotional distinctions emerges especially across different cultures. In this paper, we investigate the semantic, cultural, and social aspects of emoticon usage on Twitter and show that emoticons are not limited to conveying a specific emotion or used as jokes, but rather are socio-cultural norms, whose meaning can vary depending on the identity of the speaker. We also demonstrate how these norms propagate through the Twitter @-reply network. We confirm our results on a large-scale dataset of over one billion Tweets from different time periods and countries.

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Evaluating hypotheses in geolocation on a very large sample of Twitter

TL;DR: Six hypotheses against a corpus consisting of all geo-tagged tweets from the US, or whose geo-tags could be inferred, in a 19% sample of Twitter history are examined, including that spelling variants and hashtags are strong predictors of location.
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Understanding emojis: Cultural influences in interpretation and choice of emojis

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Sag's mit einem Lächeln - Emotionsbasierte Qualitätsverbesserung

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Emoticon Recommendation System Reflecting User Individuality - A Preliminary Survey of Emoticon Use.

TL;DR: This research aims to propose an emoticon recommendation system that considers individual differences, and conducts a survey about the use of emoticons.
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Gender and language variation on the comments of viral youtube videos

TL;DR: The authors analyzed the language variations between female and male comments on YouTube viral videos as to abbreviations, emojis, laughter variants, and spelling variants of personal pronouns, utilizing a mixed-method design.
References
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TL;DR: The Linguistic Inquiry and Word Count (LIWC) system as discussed by the authors is a text analysis system that counts words in psychologically meaningful categories to detect meaning in a wide variety of experimental settings, including to show attentional focus, emotionality, social relationships, thinking styles and individual differences.
Proceedings Article

Measuring User Influence in Twitter: The Million Follower Fallacy

TL;DR: An in-depth comparison of three measures of influence, using a large amount of data collected from Twitter, is presented, suggesting that topological measures such as indegree alone reveals very little about the influence of a user.
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An evolutionary approach to norms

TL;DR: In this article, the emergence and stability of behavioral norms in the context of a game played by people of limited rationality is analyzed with a computer simulation based upon the evolutionary principle that strategies shown to be relatively effective will be used more in the future than less effective strategies.
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The Dissemination of Culture: A Model with Local Convergence and Global Polarization

TL;DR: In this paper, an agent-based adaptive model is proposed to reveal the effects of a mechanism of convergent social influence, where actors are placed at fixed sites and the basic premise is that the more similar an actor is to a neighbor, the more likely that that actor will adopt one of the neighbor's traits.
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