Flocks, herds and schools: A distributed behavioral model
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Stigmergy, self-organization, and sorting in collective robotics
Artificial Life
Future Generation Computer Systems
Racial Homophily and Its Persistence in Newcomers' Social Networks
Organization Science
Recognizing contextual polarity in phrase-level sentiment analysis
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Why we twitter: understanding microblogging usage and communities
Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis
V-like formations in flocks of artificial birds
Artificial Life
Why are they excited?: identifying and explaining spikes in blog mood levels
EACL '06 Proceedings of the Eleventh Conference of the European Chapter of the Association for Computational Linguistics: Posters & Demonstrations
Living technology: Exploiting life's principles in technology
Artificial Life
An unobtrusive behavioral model of "gross national happiness"
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
What is Twitter, a social network or a news media?
Proceedings of the 19th international conference on World wide web
Investigating Homophily in Online Social Networks
WI-IAT '10 Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Sentiment propagation in social networks: a case study in livejournal
SBP'10 Proceedings of the Third international conference on Social Computing, Behavioral Modeling, and Prediction
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Improving news ranking by community tweets
Proceedings of the 21st international conference companion on World Wide Web
Sentiment strength detection for the social web
Journal of the American Society for Information Science and Technology
Leveraging relationships in social networks for sentiment analysis
Proceedings of the 18th Brazilian symposium on Multimedia and the web
Modeling online collective emotions
Proceedings of the 2012 workshop on Data-driven user behavioral modelling and mining from social media
Community Evolution and Engagement through Assortative Mixing in Online Social Networks
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
Dissemination Patterns and Associated Network Effects of Sentiments in Social Networks
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
Social structure and depression in TrevorSpace
Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing
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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."