Analyzing Answer Acceptance on Stack Overflow Using the Asker's Participation in Answer Comments

CQA platforms face problems, particularly inactive participants and low-quality content, that hurt long-term sustainability (Srba & Bielikova, 2016). Recent CQA studies have revealed the great value of answer comments in contributing to crowdsourced knowledge and investigating answer acceptance. A practical step forward from recent work aiming to remedy the sustainability issue of CQA, this study has offered insights into the impact of the asker generally participating in the comments section of an answer on the acceptance of that answer on Stack Overflow (a technical CQA site). A literature review was carefully carried out to show the general scope of CQA research and position this study with related work. Compared with existing work, this study demonstrates its novelty by using attributes derived from answer comments (e.g., AskerInCommentsOrNot) in the models for analyzing answer acceptance. The data collected was broadly about machine learning (ML) along with various topics, making it representative of Stack Overflow. The 19,555 records were analyzed using the Chi-Square test and Logistic Regression. The findings indicate that the asker's participation in the comments section of an answer is associated with the acceptance of that answer, and answers with more of the asker's participation in answer comments are more likely to be accepted. Broadly, this research supports the idea that answer comments are a valuable type of social interaction and feedback in CQA. This research also has beneficial implications for stakeholders on Stack Overflow and potentially technical CQA, including facilitating CQA flow, effectively evaluating helpful information, improving system designs, and motivating user participation.