Knowledge Sharing in Online Discussion Threads
Yuyang Liang · 2017
As an important category of user-generated content (UGC) community, Question and Answer (Q&A) community offers internet users opportunities to ask questions and share knowledge with others. In order to understand how the ratings of knowledge contribution quality correlate with the way knowledge is being shared in discussion threads, the study examines user behaviors and profiles in a large knowledge sharing community, /r/Techsupport, a discussion based Q&A site in Reddit.com concerning internet and technology problems. Negative binomial regressions and negative binomial mixed models are built to investigate the relationships among thread structure, level of user activity, user profiles and the ratings of threads and comments in the community. Results indicate that in the better rated threads, the structures tend to be more centralized with heterogeneous participants discussing the problem at a deeper level. Meanwhile, contributions with good ratings are more likely to be produced by users who are more engaged in commenting behaviors.