Group formation in large social networks: membership, growth, and evolution
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Measurement and analysis of online social networks
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
All My People Right Here, Right Now: management of group co-presence on a social networking site
Proceedings of the ACM 2009 international conference on Supporting group work
Feasibility of structural network clustering for group-based privacy control in social networks
Proceedings of the Sixth Symposium on Usable Privacy and Security
Bridging the gap between physical location and online social networks
Proceedings of the 12th ACM international conference on Ubiquitous computing
SOCIALCOM '10 Proceedings of the 2010 IEEE Second International Conference on Social Computing
Community detection in Social Media
Data Mining and Knowledge Discovery
Cross-domain community detection in heterogeneous social networks
Personal and Ubiquitous Computing
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Discovering groups of online friends who go to the same physical places has numerous potential applications including privacy management, friend recommendation, and contact grouping as in Google+ circles. Until recently, little information was available about places visited by users of online social networking services, so community detection on the social graph could not take this into account. With the rise of services such as Foursquare, Gowalla, and Facebook Places, where users check in to named venues and share their location with their friends, we now have the right data to make this possible. In this work, we propose a way to extract place-focused communities from the social graph by annotating its edges with check-in information. Using traces from two online social networks with location sharing, we show that we can extract groups of friends who meet face-to-face, with many possible benefits for online social services.