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Purpose: Drawing on the cognitive-functional model of emotions and emotional contagion, the authors aim to examine the role of negative emotions in the diffusion of cancer tweets. Design/methodology/approach: Using an integrated approach of social network and text analytics, the authors analyzed 142,883 cancer tweets from February to March 2018. The roles of negative emotions, emotional contagion, cancer themes and user influence on the diffusion of cancer tweets were examined. Findings: Results indicated that cancer tweets expressing negativity and anger diffused more widely, while those expressing sadness or fear were less likely to diffuse. However, contrary to the authors' expectation, cancer tweets expressing negative emotions (i.e. negativity, anger and fear) were less likely to arouse similar emotions among retweets, thus suggesting that emotions in cancer tweets were not as contagious as they seemed. Finally, user influence was the most important factor explaining the diffusion of cancer tweets, although cancer-related themes (i.e. affective, informative and social) had marginal effects on likelihood of diffusion. Originality/value: Using a novel integrated social network–text analytics approach, the authors found that to understand cancer tweets' diffusion, it is critical to go beyond examining the content of tweets about cancer and the influence of messengers – the virality of cancer tweets is inextricable from the negative emotions. [ABSTRACT FROM AUTHOR]

This study examines the proliferation of COVID-19 misinformation through Plandemic—a pseudo-documentary of COVID-19 conspiracy theories—on social media and examines how factors such as (a) themes of misinformation, (b) types of misinformation, (c) sources of misinformation, (d) emotions of misinformation, and (e) fact-checking labels amplify or attenuate online misinformation during the early days of the pandemic. Using CrowdTangle, a Facebook API, we collected a total of 5732 publicly available Facebook pages posts containing Plandemic -related keywords from January 1 to December 19, 2020. A random sample of 600 posts was subsequently coded, and the data were analyzed using negative binomial regression to examine factors associated with amplification and attenuation. Overall, the extended an extended Social Amplification of Risk Framework (SARF) provided a theoretical lens to understand why certain misinformation was amplified, while others were attenuated. As for posts with misinformation, results showed that themes related to private firms, treatment and prevention of virus transmission, diagnosis and health impacts, virus origins, and social impact were more likely to be amplified. While the different types of misinformation (manipulated, fabricated, or satire) and emotions were not associated with amplification, the type of fact-check labels did influence the virality of misinformation. Specifically, posts that were flagged as false by Facebook were more likely to be amplified, while the virality of posts flagged as containing partially false information was attenuated. Theoretical and practical implications were discussed. • "Manipulated"/"fabricated" content were the most prevalent forms of misinformation. • Emotions were not associated COVID-19 amplification. • Posts flagged containing partially false information were not amplified. [ABSTRACT FROM AUTHOR]