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Do You Really Know if It’s True? How Asking Users to Rate Stories Affects Belief in Fake News on Social Media

Author

Listed:
  • Patricia L. Moravec

    (Information, Risk, and Operations Management Department, McCombs School of Business, University of Texas, Austin, Texas 78705)

  • Antino Kim

    (Operations and Decision Technologies Department, Kelley School of Business, Indiana University, Bloomington, Indiana 47405)

  • Alan R. Dennis

    (Operations and Decision Technologies Department, Kelley School of Business, Indiana University, Bloomington, Indiana 47405)

  • Randall K. Minas

    (Information Technology Management, Shidler College of Business, University of Hawai’i at Manoa, Honolulu, Hawaii 96822)

Abstract
Research has shown that consuming ratings influences purchase decisions in e-commerce and also has modest effects on belief in news articles on social media. However, we do not know if the act of creating a rating influences belief in online news stories. Unlike e-commerce settings in which ratings typically come from those who have personally used the product or service, social media users who submit their ratings for news articles typically lack firsthand knowledge of the events reported in the news, making it difficult for most users to rate news articles accurately. We propose that one key benefit of user ratings in the context of news on social media lies in triggering users who create the ratings (as opposed to consume the ratings) to realize that they lack this firsthand knowledge, thus inducing them to become more skeptical of articles they see. We asked 68 social media users to assess the believability of 42 social media articles and measured their cognitive activity using electroencephalography. We found that asking users to rate articles using a self-referential question induced them to think more critically—as indicated by increased activation in the medial prefrontal cortex and dorsolateral prefrontal cortex—and made them less likely to believe the articles. The effect extended to subsequent articles; after being asked to rate an article, users were less likely to believe other articles that followed it whether they were asked to rate them or not. Overall, our findings suggest that asking users to evaluate the truthfulness of articles using self-referential rating questions may not only produce rating information that could be used by others later in time, but also has an immediate benefit of inducing users to think more critically about all articles they see.

Suggested Citation

  • Patricia L. Moravec & Antino Kim & Alan R. Dennis & Randall K. Minas, 2022. "Do You Really Know if It’s True? How Asking Users to Rate Stories Affects Belief in Fake News on Social Media," Information Systems Research, INFORMS, vol. 33(3), pages 887-907, September.
    • Handle: RePEc:inm:orisre:v:33:y:2022:i:3:p:887-907
    DOI: 10.1287/isre.2021.1090
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    References listed on IDEAS

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    1. Gersick, Connie J. G. & Hackman, J. Richard, 1990. "Habitual routines in task-performing groups," Organizational Behavior and Human Decision Processes, Elsevier, vol. 47(1), pages 65-97, October.
    2. Hunt Allcott & Matthew Gentzkow, 2017. "Social Media and Fake News in the 2016 Election," NBER Working Papers 23089, National Bureau of Economic Research, Inc.
    3. Nikolay Archak & Anindya Ghose & Panagiotis G. Ipeirotis, 2011. "Deriving the Pricing Power of Product Features by Mining Consumer Reviews," Management Science, INFORMS, vol. 57(8), pages 1485-1509, August.
    4. Dezhi Yin & Sabyasachi Mitra & Han Zhang, 2016. "Research Note—When Do Consumers Value Positive vs. Negative Reviews? An Empirical Investigation of Confirmation Bias in Online Word of Mouth," Information Systems Research, INFORMS, vol. 27(1), pages 131-144, March.
    5. Gordon Pennycook & Adam Bear & Evan T. Collins & David G. Rand, 2020. "The Implied Truth Effect: Attaching Warnings to a Subset of Fake News Headlines Increases Perceived Accuracy of Headlines Without Warnings," Management Science, INFORMS, vol. 66(11), pages 4944-4957, November.
    6. Xianghua Lu & Sulin Ba & Lihua Huang & Yue Feng, 2013. "Promotional Marketing or Word-of-Mouth? Evidence from Online Restaurant Reviews," Information Systems Research, INFORMS, vol. 24(3), pages 596-612, September.
    7. Sparks, Beverley A. & Browning, Victoria, 2011. "The impact of online reviews on hotel booking intentions and perception of trust," Tourism Management, Elsevier, vol. 32(6), pages 1310-1323.
    8. Hunt Allcott & Matthew Gentzkow, 2017. "Social Media and Fake News in the 2016 Election," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 211-236, Spring.
    9. Yi-Chun (Chad) Ho & Junjie Wu & Yong Tan, 2017. "Disconfirmation Effect on Online Rating Behavior: A Structural Model," Information Systems Research, INFORMS, vol. 28(3), pages 626-642, September.
    10. Marc Fischer & Sönke Albers & Nils Wagner & Monika Frie, 2011. "Practice Prize Winner --Dynamic Marketing Budget Allocation Across Countries, Products, and Marketing Activities," Marketing Science, INFORMS, vol. 30(4), pages 568-585, July.
    11. JaeHong Park & Prabhudev Konana & Bin Gu & Alok Kumar & Rajagopal Raghunathan, 2013. "Information Valuation and Confirmation Bias in Virtual Communities: Evidence from Stock Message Boards," Information Systems Research, INFORMS, vol. 24(4), pages 1050-1067, December.
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