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      Identifying and Analyzing Health-Related Themes in Disinformation Shared by Conservative and Liberal Russian Trolls on Twitter


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          To combat health disinformation shared online, there is a need to identify and characterize the prevalence of topics shared by trolls managed by individuals to promote discord. The current literature is limited to a few health topics and dominated by vaccination. The goal of this study is to identify and analyze the breadth of health topics discussed by left (liberal) and right (conservative) Russian trolls on Twitter. We introduce an automated framework based on mixed methods including both computational and qualitative techniques. Results suggest that Russian trolls discussed 48 health-related topics, ranging from diet to abortion. Out of the 48 topics, there was a significant difference ( p-value ≤ 0.004) between left and right trolls based on 17 topics. Hillary Clinton’s health during the 2016 election was the most popular topic for right trolls, who discussed this topic significantly more than left trolls. Mental health was the most popular topic for left trolls, who discussed this topic significantly more than right trolls. This study shows that health disinformation is a global public health threat on social media for a considerable number of health topics. This study can be beneficial for researchers who are interested in political disinformation and health monitoring, communication, and promotion on social media by showing health information shared by Russian trolls.

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            The spread of true and false news online

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              Systematic Literature Review on the Spread of Health-related Misinformation on Social Media

              Contemporary commentators describe the current period as “an era of fake news” in which misinformation, generated intentionally or unintentionally, spreads rapidly. Although affecting all areas of life, it poses particular problems in the health arena, where it can delay or prevent effective care, in some cases threatening the lives of individuals. While examples of the rapid spread of misinformation date back to the earliest days of scientific medicine, the internet, by allowing instantaneous communication and powerful amplification has brought about a quantum change. In democracies where ideas compete in the marketplace for attention, accurate scientific information, which may be difficult to comprehend and even dull, is easily crowded out by sensationalized news. In order to uncover the current evidence and better understand the mechanism of misinformation spread, we report a systematic review of the nature and potential drivers of health-related misinformation. We searched PubMed, Cochrane, Web of Science, Scopus and Google databases to identify relevant methodological and empirical articles published between 2012 and 2018. A total of 57 articles were included for full-text analysis. Overall, we observe an increasing trend in published articles on health-related misinformation and the role of social media in its propagation. The most extensively studied topics involving misinformation relate to vaccination, Ebola and Zika Virus, although others, such as nutrition, cancer, fluoridation of water and smoking also featured. Studies adopted theoretical frameworks from psychology and network science, while co-citation analysis revealed potential for greater collaboration across fields. Most studies employed content analysis, social network analysis or experiments, drawing on disparate disciplinary paradigms. Future research should examine susceptibility of different sociodemographic groups to misinformation and understand the role of belief systems on the intention to spread misinformation. Further interdisciplinary research is also warranted to identify effective and tailored interventions to counter the spread of health-related misinformation online.

                Author and article information

                Role: Academic Editor
                Int J Environ Res Public Health
                Int J Environ Res Public Health
                International Journal of Environmental Research and Public Health
                23 February 2021
                February 2021
                : 18
                : 4
                [1 ]School of Information Science, University of South Carolina, Columbia, SC 29208, USA
                [2 ]School of Information Sciences, University of Illinois Urbana-Champaign, Champaign, IL 61820, USA; melundy2@ 123456illinois.edu
                [3 ]Department of Computational and Data Sciences, George Mason University, Fairfax, VA 22030, USA; fwebb2@ 123456masonlive.gmu.edu
                [4 ]Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, USA; brie@ 123456sc.edu
                [5 ]School of Journalism and Mass Communications, University of South Carolina, Columbia, SC 29208, USA; brookew@ 123456sc.edu (B.W.M.); robert.mckeever@ 123456sc.edu (R.M.)
                Author notes
                [* ]Correspondence: karami@ 123456sc.edu
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).


                Public health

                twitter, trolls, health, disinformation, text mining, topic modeling


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