The Journal of Machine Learning Research
Robust temporal processing of news
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Time period identification of events in text
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Fostering empowerment in online support groups
Computers in Human Behavior
Inferring activity time in news through event modeling
HLT-SRWS '08 Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Student Research Workshop
An interactive tool for supporting error analysis for text mining
HLT-DEMO '10 Proceedings of the NAACL HLT 2010 Demonstration Session
Language use as a reflection of socialization in online communities
LSM '11 Proceedings of the Workshop on Languages in Social Media
Modeling of stylistic variation in social media with stretchy patterns
DIALECTS '11 Proceedings of the First Workshop on Algorithms and Resources for Modelling of Dialects and Language Varieties
Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work
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This paper presents an automatic analysis method that enables efficient examination of participant behavior trajectories in online communities, which offers the opportunity to examine behavior over time at a level of granularity that has previously only been possible in small scale case study analyses. We provide an empirical validation of its performance. We then illustrate how this method offers insights into behavior patterns that enable avoiding faulty oversimplified assumptions about participation, such as that it follows a consistent trend over time. In particular, we use this method to investigate the connection between user behavior and distressful cancer events and demonstrate how this tool could assist in cancer story summarization.