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E-communities, social groups interacting online, have recently become anobject of interdisciplinary research. As with face-to-face meetings, Internetexchanges may not only include factual information but also emotionalinformation - how participants feel about the subject discussed or other groupmembers. Emotions are known to be important in affecting interaction partnersin offline communication in many ways. Could emotions in Internet exchangesaffect others and systematically influence quantitative and qualitative aspectsof the trajectory of e-communities? The development of automatic sentimentanalysis has made large scale emotion detection and analysis possible usingtext messages collected from the web. It is not clear if emotions ine-communities primarily derive from individual group members' personalities orif they result from intra-group interactions, and whether they influence groupactivities. We show the collective character of affective phenomena on a largescale as observed in 4 million posts downloaded from Blogs, Digg and BBCforums. To test whether the emotions of a community member may influence theemotions of others, posts were grouped into clusters of messages with similaremotional valences. The frequency of long clusters was much higher than itwould be if emotions occurred at random. Distributions for cluster lengths canbe explained by preferential processes because conditional probabilities forconsecutive messages grow as a power law with cluster length. For BBC forumthreads, average discussion lengths were higher for larger values of absoluteaverage emotional valence in the first ten comments and the average amount ofemotion in messages fell during discussions. Our results prove that collectiveemotional states can be created and modulated via Internet communication andthat emotional expressiveness is the fuel that sustains some e-communities.

Collective emotions online and their influence on community life