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The effectiveness of flagging content belonging to prominent individuals: The case of Donald Trump on Twitter

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  • Wallace Chipidza
  • Jie (Kevin) Yan

Abstract

There is vigorous debate as to whether influential social media platforms like Twitter and Facebook should censor objectionable posts by prominent individuals in the United States and elsewhere. A tentative middle ground is employing content moderation to signal to social media audiences that certain posts may contain objectionable information through the mechanism of flagging. Existing studies have mainly examined the effect of flagging regular users' content. To add to this emerging literature stream, we examine the effect of flagging when the underlying content is produced by a prominent individual. Leveraging Twitter's moderation activities on former U.S. President Donald Trump's tweets as our empirical setting, we employ three machine learning algorithms to estimate the effect of flagging Trump's tweets. We explore preliminary evidence as to whether these posts were retweeted less or more than expected. Our results indicate that the flagged tweets were retweeted at higher rates than expected. Our findings suggest that flagging content of prominent individuals on social media might be ineffective or even counterproductive in curbing the spread of content deemed objectionable by social media companies.

Suggested Citation

  • Wallace Chipidza & Jie (Kevin) Yan, 2022. "The effectiveness of flagging content belonging to prominent individuals: The case of Donald Trump on Twitter," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(11), pages 1641-1658, November.
  • Handle: RePEc:bla:jinfst:v:73:y:2022:i:11:p:1641-1658
    DOI: 10.1002/asi.24705
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    1. Hunt Allcott & Matthew Gentzkow, 2017. "Social Media and Fake News in the 2016 Election," NBER Working Papers 23089, National Bureau of Economic Research, Inc.
    2. 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.
    3. S. Shyam Sundar & Silvia Knobloch‐Westerwick & Matthias R. Hastall, 2007. "News cues: Information scent and cognitive heuristics," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(3), pages 366-378, February.
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    Cited by:

    1. Jiamin Pei & Le Cheng, 2024. "Representations of 5G in the Chinese and British press: a corpus-assisted critical discourse analysis," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-12, December.

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