On the bursty evolution of blogspace
WWW '03 Proceedings of the 12th international conference on World Wide Web
The Journal of Machine Learning Research
Graphs over time: densification laws, shrinking diameters and possible explanations
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Neo-tribes: the power and potential of online communities in health care
Communications of the ACM - Personal information management
Structure and evolution of online social networks
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Social Capital in Friendship-Event Networks
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
A framework for community identification in dynamic social networks
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Socio-semantic conversational information access
Proceedings of the 21st international conference companion on World Wide Web
Multi-mediated community structure in a socio-technical network
Proceedings of the 2nd International Conference on Learning Analytics and Knowledge
Finding influencers in networks using social capital
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Social moms and health: a multi-platform analysis of mommy communities
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
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Social networks are typically constructed based on explicit and well-defined relationships among individuals. In this paper, we describe another class of social networks, known as implicit affinity networks, where links are implicit in the patterns of natural affinities among individuals. An effective mathematical formulation of social capital based on implicit and explicit connections is given. Results with two Web communities, one focused on people's interests and one focused on people's blogs, exhibit rich dynamics and show interesting patterns of community evolution.