Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Scientific Computing
Information Systems Research
Group formation in large social networks: membership, growth, and evolution
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
WINE '08 Proceedings of the 4th International Workshop on Internet and Network Economics
Networks Evolving Step by Step: Statistical Analysis of Dyadic Event Data
ASONAM '09 Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining
Anatomy of the long tail: ordinary people with extraordinary tastes
Proceedings of the third ACM international conference on Web search and data mining
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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Health communities play an important role in helping patients cope with chronic disease. We analyze the vitality of these groups, in terms of their ability to attract new members and foster discussion. We present methods for performing and interpreting event history analysis with many dynamic features that are only partially observed and are highly correlated, which arise from censoring to protect privacy and the natural growth of event-count-based features respectively. We apply this methodology to identify the factors that contribute to group vitality in a diabetes community. Our findings suggest that uniformly advertising popular groups was detrimental to the diversity of popular groups, limiting the growth of the overall community. We also identified three different modes of behavior for long term members and a strategic opportunity for community managers to recruit them for leadership in less popular groups.