Literature DB >> 21554117

Happiness is assortative in online social networks.

Johan Bollen1, Bruno Gonçalves, Guangchen Ruan, Huina Mao.   

Abstract

Online social networking communities may exhibit highly complex and adaptive collective behaviors. Since emotions play such an important role in human decision making, how online networks modulate human collective mood states has become a matter of considerable interest. In spite of the increasing societal importance of online social networks, it is unknown whether assortative mixing of psychological states takes place in situations where social ties are mediated solely by online networking services in the absence of physical contact. Here, we show that the general happiness, or subjective well-being (SWB), of Twitter users, as measured from a 6-month record of their individual tweets, is indeed assortative across the Twitter social network. Our results imply that online social networks may be equally subject to the social mechanisms that cause assortative mixing in real social networks and that such assortative mixing takes place at the level of SWB. Given the increasing prevalence of online social networks, their propensity to connect users with similar levels of SWB may be an important factor in how positive and negative sentiments are maintained and spread through human society. Future research may focus on how event-specific mood states can propagate and influence user behavior in "real life."

Entities:  

Mesh:

Year:  2011        PMID: 21554117     DOI: 10.1162/artl_a_00034

Source DB:  PubMed          Journal:  Artif Life        ISSN: 1064-5462            Impact factor:   0.667


  29 in total

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7.  The Effect of Bad News and CEO Apology of Corporate on User Responses in Social Media.

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8.  Predicting national suicide numbers with social media data.

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9.  Quantifying collective attention from tweet stream.

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10.  Testing Propositions Derived from Twitter Studies: Generalization and Replication in Computational Social Science.

Authors:  Hai Liang; King-Wa Fu
Journal:  PLoS One       Date:  2015-08-19       Impact factor: 3.240

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