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This paper presents an automatic analysis method that en-ables efficient examination of participant behavior trajecto-ries in online communities. This method offers the opportu-nity to examine behavior over time at a level of granularity that has previously only been possible in small scale case study analyses, and thus complements both existing qualita-tive and quantitative methodologies. We provide an empiri-cal validation of its performance. We then illustrate how this method offers insights into behavior patterns that enable avoiding faulty oversimplified assumptions about participa-tion, such as that it follows a consistent trend over time. In particular, we use this method to investigate the con-nection between user behavior and distressful cancer events and demonstrate how this tool could assist in understanding participation trajectories in online medical support commu-nities better so we are better able to design environments that meet the needs of participants.
Wen et al. (Sat,) studied this question.