An Analytical Framework for Understanding Knowledge-Sharing Processes in Online Q&A Communities

Online communities have become popular knowledge sources for both individuals and organizations. Computer-mediated communication research shows that communication patterns play an important role in the collaborative efforts of online knowledge-sharing activities. Existing research is mainly focused on either user egocentric positions in communication networks or communication patterns at the community level. Very few studies examine thread-level communication and process patterns and their impacts on the effectiveness of knowledge sharing. In this study, we fill this research gap by proposing an innovative analytical framework for understanding thread-level knowledge sharing in online Q&A communities based on dialogue act theory, network analysis, and process mining. More specifically, we assign a dialogue act tag for each post in a discussion thread to capture its conversation purpose and then apply graph and process mining algorithms to examine knowledge-sharing processes. Our results, which are based on a real support forum dataset, show that the proposed analytical framework is effective in identifying important communication, conversation, and process patterns that lead to helpful knowledge sharing in online Q&A communities.

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