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Studying effectiveness of Web search for fact checking

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  • Maram Hasanain
  • Tamer Elsayed

Abstract

Web search is commonly used by fact checking systems as a source of evidence for claim verification. In this work, we demonstrate that the task of retrieving pages useful for fact checking, called evidential pages, is indeed different from the task of retrieving topically relevant pages that are typically optimized by search engines; thus, it should be handled differently. We conduct a comprehensive study on the performance of retrieving evidential pages over a test collection we developed for the task of re‐ranking Web pages by usefulness for fact‐checking. Results show that pages (retrieved by a commercial search engine) that are topically relevant to a claim are not always useful for verifying it, and that the engine's performance in retrieving evidential pages is weakly correlated with retrieval of topically relevant pages. Additionally, we identify types of evidence in evidential pages and some linguistic cues that can help predict page usefulness. Moreover, preliminary experiments show that a retrieval model leveraging those cues has a higher performance compared to the search engine. Finally, we show that existing systems have a long way to go to support effective fact checking. To that end, our work provides insights to guide design of better future systems for the task.

Suggested Citation

  • Maram Hasanain & Tamer Elsayed, 2022. "Studying effectiveness of Web search for fact checking," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(5), pages 738-751, May.
  • Handle: RePEc:bla:jinfst:v:73:y:2022:i:5:p:738-751
    DOI: 10.1002/asi.24577
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    References listed on IDEAS

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    1. Tefko Saracevic, 2007. "Relevance: A review of the literature and a framework for thinking on the notion in information science. Part III: Behavior and effects of relevance," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(13), pages 2126-2144, November.
    2. Julian Unkel & Alexander Haas, 2017. "The effects of credibility cues on the selection of search engine results," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(8), pages 1850-1862, August.
    3. Tefko Saracevic, 2007. "Relevance: A review of the literature and a framework for thinking on the notion in information science. Part II: nature and manifestations of relevance," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(13), pages 1915-1933, November.
    4. Frances Johnson & Jennifer Rowley & Laura Sbaffi, 2016. "Exploring information interactions in the context of Google," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(4), pages 824-840, April.
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