Virtual Culture: Identity and Communication in CyberSociety
Virtual Culture: Identity and Communication in CyberSociety
Structure and evolution of online social networks
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the 2008 ACM conference on Computer supported cooperative work
Investigating social software as persuasive technology
PERSUASIVE'06 Proceedings of the First international conference on Persuasive technology for human well-being
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Investigating online social behaviors may help us to better understand and predict offline high risk behaviors in gay communities. But how can offline behaviors be predicted from online social networks? This article selects data from 26 online social network groups from QQ (a Chinese based messaging software) administered by gay communities of "W" city of Hubei Province, China. Based on online data mining, social network analysis, and offline semi-structural interviews, we argue that the ego-centric dynamical network analysis---an approach which combines partial network dynamics, individual features, and structure position together---can be used to derive the probabilistic features for predicting offline high risk behaviors (HRB). An example of HRB is "one night stands" (gays for one night: 419) for gay homosexuals.