Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
ACM Transactions on Computer-Human Interaction (TOCHI)
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Facetnet: a framework for analyzing communities and their evolutions in dynamic networks
Proceedings of the 17th international conference on World Wide Web
Temporal distance metrics for social network analysis
Proceedings of the 2nd ACM workshop on Online social networks
Analysis of an online health social network
Proceedings of the 1st ACM International Health Informatics Symposium
Patterns of temporal variation in online media
Proceedings of the fourth ACM international conference on Web search and data mining
Group Evolution Discovery in Social Networks
ASONAM '11 Proceedings of the 2011 International Conference on Advances in Social Networks Analysis and Mining
Applications of Social Network Construction and Analysis in the Medical Referral Process
DASC '11 Proceedings of the 2011 IEEE Ninth International Conference on Dependable, Autonomic and Secure Computing
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The growing amount of data in healthcare social media requires innovative new analysis methods, which are elementary to exploration of relationship dynamics, community formation, sustenance and dissolution, in a bid to understand the new roles social media play in healthcare. In this work we use network analysis to explore the temporal nature of two large diabetes social networks, with a view to enhancing our knowledge of the development of sub-community structures and cohesion factors. Current results reveal how diabetes online communities are very dynamic, suggesting diabetes patients are usually actively engaged for periods of less than a year, typically immediately following diagnosis. The presented empirical evidence inform future online intervention strategies for promoting health behavior and lifestyle changes among people with diabetes.