Achieving application requirements
Distributed systems
Graph drawing by force-directed placement
Software—Practice & Experience
Hubs, authorities, and communities
ACM Computing Surveys (CSUR)
Exploratory Social Network Analysis with Pajek
Exploratory Social Network Analysis with Pajek
Statistical properties of community structure in large social and information networks
Proceedings of the 17th international conference on World Wide Web
Planetary-scale views on a large instant-messaging network
Proceedings of the 17th international conference on World Wide Web
Microscopic evolution of social networks
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Analyzing patterns of user content generation in online social networks
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Temporal distance metrics for social network analysis
Proceedings of the 2nd ACM workshop on Online social networks
Temporal visualization of social network dynamics: prototypes for nation of neighbors
SBP'11 Proceedings of the 4th international conference on Social computing, behavioral-cultural modeling and prediction
Community insights: helping community leaders enhance the value of enterprise online communities
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
CommunityCompare: visually comparing communities for online community leaders in the enterprise
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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In this paper, we present a model for temporal analysis of an online discussion group, also known as an online forum. We used a social network model and investigated an online melanoma forum in detail. Our overall goal is to develop methods that quantify the responsiveness of the interactions in online forums. In particular, we are interested in identifying the evolutional stages through which online forums transition. The evolutional stages show if a forum is growing, shrinking, or in a state of equilibrium. In the work we present here, we measured the creation of threads, the creation of responses and the number of new users, as well as the topology of the melanoma network across an eight-year timeframe in order to measure network activity. We defined a response function in terms of the number of threads receiving a response, the number of threads not receiving a response, and the delay in response time. We used the response function as an approximation of the discussion group's utility. We found three distinct evolutional stages over the eight-year period and a range of response levels, in some cases determined by the severity of the disease under discussion. Our findings have implications for both forum owners and members. Each can assess and subsequently adjust the level of online interaction to improve the usefulness of the forum. Further, the assessed activity level of a forum may be useful for online health seekers as they decide whether or not to join a particular forum.