Moral Emotions Shape the Virality of COVID-19 Misinformation on Social Media
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Abstract (arXiv)
While false rumors pose a threat to the successful overcoming of the COVID-19 pandemic, an understanding of how rumors diffuse in online social networks is - even for non-crisis situations - still in its infancy. Here we analyze a large sample consisting of COVID-19 rumor cascades from Twitter that have been fact-checked by third-party organizations. The data comprises N=10,610 rumor cascades that have been retweeted more than 24 million times. We investigate whether COVID-19 misinformation spreads more viral than the truth and whether the differences in the diffusion of true vs. false rumors can be explained by the moral emotions they carry. We observe that, on average, COVID-19 misinformation is more likely to go viral than truthful information. However, the veracity effect is moderated by moral emotions: false rumors are more viral than the truth if the source tweets embed a high number of other-condemning emotion words, whereas a higher number of self-conscious emotion words is linked to a less viral spread. The effects are pronounced both for health misinformation and false political rumors. These findings offer insights into how true vs. false rumors spread and highlight the importance of considering emotions from the moral emotion families in social media content.
Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 Feb 2022.
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Citing papers per year: 2022: 2; 2023: 5; 2024: 1; 2025: 1; 2026: 3.
12 papers.
- 2022Memory-Guided Multi-View Multi-Domain Fake News Detectioncited by 31
- 2023Emotion Detection for Misinformation: A Reviewcited by 20
- 2022Characterizing Multi-Domain False News and Underlying User Effects on Chinese Weibocited by 8
- 2023WSDMS: Debunk Fake News via Weakly Supervised Detection of Misinforming Sentences with Contextualized Social Wisdomcited by 6
- 2023Which linguistic cues make people fall for fake news? A comparison of cognitive and affective processingcited by 3
- 2026Moral Outrage Shapes Commitments Beyond Attention: Multimodal Moral Emotions on YouTube in Korea and the UScited by 2
- 2024Semantic Evolvement Enhanced Graph Autoencoder for Rumor Detectioncited by 1
- 2023Characterizing the Emotion Carriers of COVID-19 Misinformation and Their Impact on Vaccination Outcomes in India and the United Statescited by 0
- 2023Digital Emotion Regulation on Social Mediacited by 0
- 2025Queuing for Civility: Regulating Emotions and Reducing Toxicity in Digital Discoursecited by 0
- 2026Angry but Accurate: Detecting and Profiling the Counter-Misinformation Ecosystem on Twittercited by 0
- 2026Predicting, Evaluating, and Explaining Top Misinformation Spreaders via Archetypal User Behaviorcited by 0
- 2026Predicting, Evaluating, and Explaining Top Misinformation Spreaders via Archetypal User Behavior17 Aug 2026
- 2026Angry but Accurate: Detecting and Profiling the Counter-Misinformation Ecosystem on Twitter3 Jul 2026
- 2026Moral Outrage Shapes Commitments Beyond Attention: Multimodal Moral Emotions on YouTube in Korea and the US29 Jan 2026
- 2025Queuing for Civility: Regulating Emotions and Reducing Toxicity in Digital Discourse31 Aug 2025
- 2024Semantic Evolvement Enhanced Graph Autoencoder for Rumor Detection24 Apr 2024
- 2023Which linguistic cues make people fall for fake news? A comparison of cognitive and affective processing2 Dec 2023
- 2023Emotion Detection for Misinformation: A Review1 Nov 2023
- 2023WSDMS: Debunk Fake News via Weakly Supervised Detection of Misinforming Sentences with Contextualized Social Wisdom25 Oct 2023
- 2023Digital Emotion Regulation on Social Media25 Jul 2023
- 2023Characterizing the Emotion Carriers of COVID-19 Misinformation and Their Impact on Vaccination Outcomes in India and the United States24 Jun 2023
- 2022Memory-Guided Multi-View Multi-Domain Fake News Detection26 Jun 2022
- 2022Characterizing Multi-Domain False News and Underlying User Effects on Chinese Weibo6 May 2022