Understanding Participant Behavior Trajectories in Online Health Support Groups Using Automatic Extraction Methods
Association for Computing Machinery
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.