Collective Emotions Online and Their Influence on Community Life

Abstract

BackgroundE-communities, social groups interacting online, have recently become an object of interdisciplinary research. As with face-to-face meetings, Internet exchanges may not only include factual information but also emotional information – how participants feel about the subject discussed or other group members. Emotions in turn are known to be important in affecting interaction partners in offline communication in many ways. Could emotions in Internet exchanges affect others and systematically influence quantitative and qualitative aspects of the trajectory of e-communities? The development of automatic sentiment analysis has made large scale emotion detection and analysis possible using text messages collected from the web. However, it is not clear if emotions in e-communities primarily derive from individual group members' personalities or if they result from intra-group interactions, and whether they influence group activities.Methodology/Principal FindingsHere, for the first time, we show the collective character of affective phenomena on a large scale as observed in four million posts downloaded from Blogs, Digg and BBC forums. To test whether the emotions of a community member may influence the emotions of others, posts were grouped into clusters of messages with similar emotional valences. The frequency of long clusters was much higher than it would be if emotions occurred at random. Distributions for cluster lengths can be explained by preferential processes because conditional probabilities for consecutive messages grow as a power law with cluster length. For BBC forum threads, average discussion lengths were higher for larger values of absolute average emotional valence in the first ten comments and the average amount of emotion in messages fell during discussions.Conclusions/SignificanceOverall, our results prove that collective emotional states can be created and modulated via Internet communication and that emotional expressiveness is the fuel that sustains some e-communities.

Predicting Code-switching in Multilingual Communication for Immigrant Communities

“…Emoticons have mostly been used in the context of sentiment analysis (e.g. Volkova et al (2013), Chmiel et al (2011)). Park et al (2014) studied how the use of emoticons differ across cultures in Twitter data.…”

Sentiment and Factual Transitions in Online Medical Forums

“…The studies of sentiment propagation in social networks is an emerging area of sentiment analysis [7,19]. Results obtained for three online communities have shown that the original polarity is preserved in the follow-up posts: negative posts mainly trigger negative follow-ups, positive posts -positive followups, and neutrality brings forth neutrality [7].…”

“…Results obtained for three online communities have shown that the original polarity is preserved in the follow-up posts: negative posts mainly trigger negative follow-ups, positive posts -positive followups, and neutrality brings forth neutrality [7]. Sentiment propagation between two Twitter interlocutors has been studied in several works, [13] being the most cited.…”

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Damping Sentiment Analysis in Online Communication: Discussions, Monologs and Dialogs

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