PeopleGarden: creating data portraits for users
Proceedings of the 12th annual ACM symposium on User interface software and technology
HICSS '04 Proceedings of the Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04) - Track 4 - Volume 4
Tracking Information Epidemics in Blogspace
WI '05 Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence
Proceedings of the 2006 international workshop on Mining software repositories
On the evolution of user interaction in Facebook
Proceedings of the 2nd ACM workshop on Online social networks
Characterizing user behavior in online social networks
Proceedings of the 9th ACM SIGCOMM conference on Internet measurement conference
Clustering of time series data-a survey
Pattern Recognition
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
A binary decision diagram based approach for mining frequent subsequences
Knowledge and Information Systems
Tagging and linking web forum posts
CoNLL '10 Proceedings of the Fourteenth Conference on Computational Natural Language Learning
An Analysis of Communities in Different Types of Online Forums
ASONAM '10 Proceedings of the 2010 International Conference on Advances in Social Networks Analysis and Mining
Leadership discovery when data correlatively evolve
World Wide Web
The Joint Inference of Topic Diffusion and Evolution in Social Communities
ICDM '11 Proceedings of the 2011 IEEE 11th International Conference on Data Mining
Bursty event detection from collaborative tags
World Wide Web
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Online forums are rich sources of information about user communication activity over time. Finding temporal patterns in online forum communication threads can advance our understanding of the dynamics of conversations. The main challenge of temporal analysis in this context is the complexity of forum data. There can be thousands of interacting users, who can be numerically described in many different ways. Moreover, user characteristics can evolve over time. We propose an approach that decouples temporal information about users into sequences of user events and inter-event times. We develop a new feature space to represent the event sequences as paths, and we model the distribution of the inter-event times. We study over 30,000 users across four Internet forums, and discover novel patterns in user communication. We find that users tend to exhibit consistency over time. Furthermore, in our feature space, we observe regions that represent unlikely user behaviors. Finally, we show how to derive a numerical representation for each forum, and we then use this representation to derive a novel clustering of multiple forums.