Going beyond fact-checking to fight health misinformation: A multi-level analysis of the Twitter response to health news stories

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7 Citations (Scopus)


Health misinformation has become an unfortunate truism of social media platforms, where lies could spread faster than truth. Despite considerable work devoted to suppressing fake news, health misinformation, including low-quality health news, persists and even increases in recent years. One promising approach to fighting bad information is studying the temporal and sentiment effects of health news stories and how they are discussed and disseminated on social media platforms like Twitter. As part of the effort of searching for innovative ways to fight health misinformation, this study analyzes a dataset of more than 1600 objectively and independently reviewed health news stories published over a 10-year span and nearly 50,000 Twitter posts responding to them. Specifically, it examines the source credibility of health news circulated on Twitter and the temporal, sentiment features of the tweets containing or responding to the health news reports. The results show that health news stories that are rated low by experts are discussed more, persist longer, and produce stronger sentiments than highly rated ones in the tweetosphere. However, the highly rated stories retained a fresh interest in the form of new tweets for a longer period. An in-depth understanding of the characteristics of health news distribution and discussion is the first step toward mitigating the surge of health misinformation. The findings provide insights into understanding the mechanism of health information dissemination on social media and practical implications to fight and mitigate health misinformation on digital media platforms.

Original languageEnglish
Article number102626
Number of pages11
JournalInternational Journal of Information Management
Early online date24 Jan 2023
Publication statusPublished - Jun 2023

Scopus Subject Areas

  • Information Systems and Management
  • Artificial Intelligence
  • Information Systems
  • Library and Information Sciences
  • Marketing
  • Management Information Systems
  • Computer Networks and Communications

User-Defined Keywords

  • Health misinformation
  • Health news
  • Information quality
  • Sentiment analysis
  • Source credibility
  • Tweet


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