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Understanding the Humans Behind Online Misinformation: An Observational Study Through the Lens of the COVID-19 Pandemic (2310.08483v2)

Published 12 Oct 2023 in cs.CL and cs.SI

Abstract: The proliferation of online misinformation has emerged as one of the biggest threats to society. Considerable efforts have focused on building misinformation detection models, still the perils of misinformation remain abound. Mitigating online misinformation and its ramifications requires a holistic approach that encompasses not only an understanding of its intricate landscape in relation to the complex issue and topic-rich information ecosystem online, but also the psychological drivers of individuals behind it. Adopting a time series analytic technique and robust causal inference-based design, we conduct a large-scale observational study analyzing over 32 million COVID-19 tweets and 16 million historical timeline tweets. We focus on understanding the behavior and psychology of users disseminating misinformation during COVID-19 and its relationship with the historical inclinations towards sharing misinformation on Non-COVID domains before the pandemic. Our analysis underscores the intricacies inherent to cross-domain misinformation, and highlights that users' historical inclination toward sharing misinformation is positively associated with their present behavior pertaining to misinformation sharing on emergent topics and beyond. This work may serve as a valuable foundation for designing user-centric inoculation strategies and ecologically-grounded agile interventions for effectively tackling online misinformation.

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References (76)
  1. Joshua D Angrist and Jörn-Steffen Pischke. 2009. Mostly harmless econometrics: An empiricist’s companion. Princeton university press.
  2. Sandra J Ball-Rokeach and Melvin L DeFleur. 1976. A dependency model of mass-media effects. Communication research (1976).
  3. Peter M Bednar and Christine Welch. 2008. Bias, Misinformation and the Paradox of Neutrality. Informing Science 11 (2008).
  4. Salil D Benegal and Lyle A Scruggs. 2018. Correcting misinformation about climate change: The impact of partisanship in an experimental setting. Climatic change 148, 1-2 (2018), 61–80.
  5. Trend of narratives in the age of misinformation. PloS one 10, 8 (2015), e0134641.
  6. You are right. I am ALARMED – But by Climate Change Counter Movement. arXiv:2004.14907 [cs.CL]
  7. Alexandre Bovet and Hernán Makse. 2019. Influence of fake news in Twitter during the 2016 US presidential election. Nature Communications (2019).
  8. CCDH. 2021. THE DISINFORMATION DOZEN. https://counterhate.com/research/the-disinformation-dozen/. Accessed: 2023-08-30.
  9. Centers for Disease Control and Prevention. 2020. CDC Museum COVID-19 Timeline. https://www.cdc.gov/museum/timeline/covid19.html.
  10. ”A Virus Has No Religion”: Analyzing Islamophobia on Twitter During the COVID-19 Outbreak. In Proc. of ACM HT 2021. ACM.
  11. Tracking Social Media Discourse About the COVID-19 Pandemic: Development of a Public Coronavirus Twitter Data Set. JMIR Public Health Surveill (2020).
  12. Inoculation theory in the post-truth era: Extant findings and new frontiers for contested science, misinformation, and conspiracy theories. Social and Personality Psychology Compass (2021).
  13. Limeng Cui and Dongwon Lee. 2020. Coaid: Covid-19 healthcare misinformation dataset. arXiv preprint arXiv:2006.00885 (2020).
  14. The spreading of misinformation online. Proceedings of the national academy of Sciences 113, 3 (2016), 554–559.
  15. The Britannica Dictionary. 2023. The Environment Vocabulary Words. https://www.britannica.com/dictionary/eb/3000-words/topic/the-environment
  16. CLIMATE-FEVER: A Dataset for Verification of Real-World Climate Claims. arXiv:2012.00614 [cs.CL]
  17. R East and JP Forgas. 2007. Mood effects on scepticism and the detection of deception. Manuscript, University of New South Wales (2007).
  18. The psychological drivers of misinformation belief and its resistance to correction. Nature Reviews Psychology (2022).
  19. EPA. 2016. Glossary of climate change terms. https://19january2017snapshot.epa.gov/climatechange/glossary-climate-change-terms_.html
  20. Coronavirus misinformation: quantifying sources and themes in the COVID-19 ‘infodemic’. JMIR Preprints 19, 10 (2020), 2020.
  21. Maarten Grootendorst. 2022. BERTopic: Neural topic modeling with a class-based TF-IDF procedure. arXiv preprint arXiv:2203.05794 (2022).
  22. Yuval Noah Harari. 2018a. 21 Lessons for the 21st Century:’Truly mind-expanding… Ultra-topical’Guardian. Random House.
  23. Yuval Noah Harari. 2018b. Yuval Noah Harari extract:‘Humans are a post-truth species’. The Guardian (2018), 1–5.
  24. Racism is a Virus: Anti-Asian Hate and Counterspeech in Social Media during the COVID-19 Crisis. In Proc. of ACM ASONAM 2021. ACM.
  25. Identifying shifts in collective attention to topics on social media. In Social, Cultural, and Behavioral Modeling: 14th International Conference, SBP-BRiMS 2021, Virtual Event, July 6–9, 2021, Proceedings 14. Springer, 224–234.
  26. Matthew J Hornsey and Kelly S Fielding. 2017. Attitude roots and Jiu Jitsu persuasion: Understanding and overcoming the motivated rejection of science. American psychologist (2017).
  27. Chun-Hua Hsiao and Kai-Yu Tang. 2021. Who captures whom–Pokémon or tourists? A perspective of the Stimulus-Organism-Response model. International Journal of Information Management (2021).
  28. COVID-19–related infodemic and its impact on public health: A global social media analysis. American J. of Tropical Medicine & Hygiene (2020).
  29. Paul T Jaeger and Natalie Greene Taylor. 2021. Arsenals of lifelong information literacy: Educating users to navigate political and current events information in world of ever-evolving misinformation. The Library Quarterly (2021).
  30. Kathleen Hall Jamieson and Joseph N Cappella. 2008. Echo chamber: Rush Limbaugh and the conservative media establishment. Oxford University Press.
  31. Shan Jiang and Christo Wilson. 2018. Linguistic Signals under Misinformation and Fact-Checking: Evidence from User Comments on Social Media. PACM-HCI 2, CSCW (2018).
  32. Sebastian Jungkunz. 2021. Political polarization during the COVID-19 pandemic. Frontiers in Political Science 3 (2021), 622512.
  33. Using Longitudinal Social Media Analysis to Understand the Effects of Early College Alcohol Use. Proc. AAAI ICWSM (2018).
  34. Optimal detection of changepoints with a linear computational cost. J. Amer. Statist. Assoc. (2012).
  35. Coronavirus Goes Viral: Quantifying the COVID-19 Misinformation Epidemic on Twitter. Cureus 12 (03 2020). https://doi.org/10.7759/cureus.7255
  36. Citizens versus the internet: Confronting digital challenges with cognitive tools. Psychological Science in the Public Interest (2020).
  37. Strategic disinformation outperforms honesty in competition for social influence. Iscience (2021).
  38. Unusual purchasing behavior during the early stages of the COVID-19 pandemic: The stimulus-organism-response approach. Journal of Retailing and Consumer Services (2020).
  39. What drives unverified information sharing and cyberchondria during the COVID-19 pandemic? European journal of information systems (2020).
  40. Misinformation during the COVID-19 outbreak in China: cultural, social and political entanglements. Big Data (2021).
  41. Technology and democracy: Understanding the influence of online technologies on political behaviour and decision-making. (2020).
  42. YouTube as a source of misinformation on COVID-19 vaccination: a systematic analysis. BMJ global health (2022).
  43. Rising tides or rising stars?: Dynamics of shared attention on Twitter during media events. PloS one 9, 5 (2014), e94093.
  44. Shahan Ali Memon and Kathleen M Carley. 2020. Characterizing covid-19 misinformation communities using a novel twitter dataset. arXiv preprint arXiv:2008.00791 (2020).
  45. The role of the crowd in countering misinformation: A case study of the COVID-19 infodemic. In Big Data 2020). IEEE.
  46. Amy I Nathanson. 2002. The unintended effects of parental mediation of television on adolescents. Media Psychology 4, 3 (2002), 207–230.
  47. Lying Words: Predicting Deception from Linguistic Styles. Personality & Social Psych Bulletin (2003).
  48. BERTweet: A pre-trained language model for English Tweets. In Proc. of EMNLP 2020: System Demonstrations. https://doi.org/10.18653/v1/2020.emnlp-demos.2
  49. Partisan polarization is the primary psychological motivation behind political fake news sharing on Twitter. American Political Science Review (2021).
  50. Evaluation of a template for countering misinformation—Real-world Autism treatment myth debunking. PloS one 14, 1 (2019), e0210746.
  51. Linguistic inquiry and word count: LIWC 2001. Mahway: Lawrence Erlbaum Associates (2001).
  52. Pew Research Center. 2021. News Consumption Across Social Media in 2021. http://tinyurl.com/ywdnbhjb. Accessed: 2023-08-29.
  53. The causes, impacts and countermeasures of COVID-19 “Infodemic”: A systematic review using narrative synthesis. Information Processing & Management (2021), 102713.
  54. Julie Posetti. 2018. News industry transformation: digital technology, social platforms and the spread of misinformation and disinformation. Journalism,‘fake news’ and disinformation: A handbook for journalism education and training. Unesco. https://bit. ly/2XLRRlA (2018).
  55. Leveraging Intra-User and Inter-User Representation Learning for Automated Hate Speech Detection. In Proc. NAACL.
  56. Daniel Romer and Kathleen Hall Jamieson. 2020. Conspiracy theories as barriers to controlling the spread of COVID-19 in the U.S. Social Science & Medicine 263 (2020), 113356. https://doi.org/10.1016/j.socscimed.2020.113356
  57. Csi: A hybrid deep model for fake news detection. In Pro. of ACM CIKM.
  58. Koustuv Saha and Amit Sharma. 2020. Causal factors of effective psychosocial outcomes in online mental health communities. In Proc. AAAI ICWSM.
  59. Dietram A Scheufele and Nicole M Krause. 2019. Science audiences, misinformation, and fake news. PNAS (2019).
  60. An exploratory study of COVID-19 misinformation on Twitter. Online social networks and media 22 (2021), 100104.
  61. Fakenewsnet: A data repository with news content, social context, and spatiotemporal information for studying fake news on social media. Big data (2020).
  62. The role of familiarity in correcting inaccurate information. Journal of experimental psychology: learning, memory, and cognition 43, 12 (2017), 1948.
  63. They might be a liar but they’re my liar: Source evaluation and the prevalence of misinformation. Political psychology 41, 1 (2020), 21–34.
  64. ThinkGlobalHealth. 2020. UPDATED: Timeline of the Coronavirus. https://www.thinkglobalhealth.org/article/updated-timeline-coronavirus.
  65. TIME. 2018. How Your Brain Tricks You Into Believing Fake News. https://time.com/5362183/the-real-fake-news-crisis/. Accessed: 2023-09-05.
  66. ” At the End of the Day Facebook Does What ItWants” How Users Experience Contesting Algorithmic Content Moderation. Proceedings of the ACM on human-computer interaction 4, CSCW2 (2020), 1–22.
  67. Inoculating the public against misinformation about climate change. Global challenges (2017).
  68. Examining the impact of sharing COVID-19 misinformation online on mental health. Scientific Reports (2022).
  69. Testing the effectiveness of correction placement and type on Instagram. The International Journal of Press/Politics (2020).
  70. Portraying Collective Spatial Attention in Twitter. KDD.
  71. William Yang Wang. 2017. ” liar, liar pants on fire”: A new benchmark dataset for fake news detection. arXiv preprint arXiv:1705.00648 (2017).
  72. Katrin Weller and Katharina Kinder-Kurlanda. 2015. Uncovering the challenges in collection, sharing and documentation: The hidden data of social media research?. In Proceedings of the International AAAI Conference on Web and Social Media, Vol. 9. 28–37.
  73. Katrin Weller and Katharina E Kinder-Kurlanda. 2016. A manifesto for data sharing in social media research. In Proceedings of the 8th ACM Conference on Web Science. 166–172.
  74. Wikipedia. 2023. Glossary of American politics. https://en.wikipedia.org/wiki/Glossary_of_American_politics
  75. World Health Organization. 2020. Rolling updates on coronavirus disease (COVID-19). https://www.who.int/emergencies/diseases/novel-coronavirus-2019/events-as-they-happen.
  76. Scalable and Generalizable Social Bot Detection through Data Selection. Proc. of the AAAI 2020 (2020).
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Authors (3)
  1. Mohit Chandra (16 papers)
  2. Anush Mattapalli (2 papers)
  3. Munmun De Choudhury (42 papers)