Group formation in large social networks: membership, growth, and evolution
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Microscopic evolution of social networks
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Supervised random walks: predicting and recommending links in social networks
Proceedings of the fourth ACM international conference on Web search and data mining
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The online and offline worlds are converging. Location-based services, ubiquitous mobile devices and on-the-go social network accessibility are blurring the distinction between in-person activities and their virtual counterpart. An important effect of this convergence is the rapid and powerful impact of offline events (meetings, conferences) on the evolution and temporal dynamics of the online connectivity between members of social and professional networks. However, these effects have been largely unexplored. We study these effects by using data from LinkedIn, a popular professional social networking site. We find that offline events may induce connectivity changes in the online network -- there is a dramatic increase in the number of connections between event attendees shortly after the date of the event. Building on these insights, we describe a non-supervised method that exploits connectivity changes temporally correlated to real world events to successfully infer more than 40% of specific event attendees. Finally, we revisit the link prediction problem by including user contributed information about off-line events to achieve higher link prediction performance.