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Users' relevance criteria for evaluating answers in a social Q&A site

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  • Soojung Kim
  • Sanghee Oh

Abstract

This study examines the criteria questioners use to select the best answers in a social Q&A site (Yahoo! Answers) within the theoretical framework of relevance research. A social Q&A site is a novel environment where people voluntarily ask and answer questions. In Yahoo! Answers, the questioner selects the answer that best satisfies his or her question and leaves comments on it. Under the assumption that the comments reflect the reasons why questioners select particular answers as the best, this study analyzed 2,140 comments collected from Yahoo! Answers during December 2007. The content analysis identified 23 individual relevance criteria in six classes: Content, Cognitive, Utility, Information Sources, Extrinsic, and Socioemotional. A major finding is that the selection criteria used in a social Q&A site have considerable overlap with many relevance criteria uncovered in previous relevance studies, but that the scope of socio‐emotional criteria has been expanded to include the social aspect of this environment. Another significant finding is that the relative importance of individual criteria varies according to topic categories. Socioemotional criteria are popular in discussion‐oriented categories, content‐oriented criteria in topic‐oriented categories, and utility criteria in self‐help categories. This study generalizes previous relevance studies to a new environment by going beyond an academic setting.

Suggested Citation

  • Soojung Kim & Sanghee Oh, 2009. "Users' relevance criteria for evaluating answers in a social Q&A site," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(4), pages 716-727, April.
    • Handle: RePEc:bla:jamist:v:60:y:2009:i:4:p:716-727
    DOI: 10.1002/asi.21026
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    Cited by:

    1. Keith Burghardt & Emanuel F Alsina & Michelle Girvan & William Rand & Kristina Lerman, 2017. "The myopia of crowds: Cognitive load and collective evaluation of answers on Stack Exchange," PLOS ONE, Public Library of Science, vol. 12(3), pages 1-19, March.
    2. Chih-Hung Peng & Dezhi Yin & Han Zhang, 2020. "More than Words in Medical Question-and-Answer Sites: A Content-Context Congruence Perspective," Information Systems Research, INFORMS, vol. 31(3), pages 913-928, September.
    3. Leila Tavakoli & Hamed Zamani & Falk Scholer & William Bruce Croft & Mark Sanderson, 2022. "Analyzing clarification in asynchronous information‐seeking conversations," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(3), pages 449-471, March.
    4. Adam Worrall & Alicia Cappello & Rachel Osolen, 2021. "The importance of socio‐emotional considerations in online communities, social informatics, and information science," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(10), pages 1247-1260, October.
    5. Warut Khern-am-nuai & Hossein Ghasemkhani & Dandan Qiao & Karthik Kannan, 2024. "The Impact of Online Q&As on Product Sales: The Case of Amazon Answer," Information Systems Research, INFORMS, vol. 35(2), pages 747-765, June.
    6. Stone, Gregory & Walton, Stephanie & Zhang, Yibo (James), 2023. "The impact of online tax community advice on individual taxpayer decision making," Advances in accounting, Elsevier, vol. 63(C).

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