Abstract
Scholars and developers have long recognized that the collections of user-generated content at social questions and answers (SQA) sites can benefit open knowledge sharing and resolve individual information needs. This has prompted strong interest in improving the quality of SQA postings, and the creation, curation, and use of these collections. While interactivity is a key feature of SQA, few studies have investigated the interaction sequence between the OP (original poster) and commenters. Drawing from Robert Taylor’s question-negotiation perspective, we posit that interaction patterns may affect SQA outcomes. Social sequence analysis (SSA) and the R package TraMineR were used to analyze the commenting sequences of Stack Overflow postings (8,132 questions and 16,598 comments). The relationships between commenting sequence structure and outcome metrics (e.g., question score, view count) were then tested with logistic regressions. Implications of the results for SQA research, SQA site design, and digital literacy training are discussed.
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This work was supported by the Nanyang Technological University Academic Research Fund (RG58/14) of Nanyang Technological University.
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Sin, SC.J., Lee, C.S., Theng, YL. (2016). Social Q&A Question-and-Comments Interactions and Outcomes: A Social Sequence Analysis. In: Morishima, A., Rauber, A., Liew, C. (eds) Digital Libraries: Knowledge, Information, and Data in an Open Access Society. ICADL 2016. Lecture Notes in Computer Science(), vol 10075. Springer, Cham. https://doi.org/10.1007/978-3-319-49304-6_37
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