Abstract

False rumors (often termed “fake news”) on social media pose a significant threat to modern societies. However, potential reasons for the widespread diffusion of false rumors have been underexplored. In this work, we analyze whether sentiment words, as well as different emotional words, in social media content explain differences in the spread of true vs. false rumors. For this purpose, we collected {varvec{N}} =126{,}301 rumor cascades from Twitter, comprising more than 4.5 million retweets that have been fact-checked for veracity. We then categorized the language in social media content to (1) sentiment (i.e., positive vs. negative) and (2) eight basic emotions (i. e., anger, anticipation, disgust, fear, joy, trust, sadness, and surprise). We find that sentiment and basic emotions explain differences in the structural properties of true vs. false rumor cascades. False rumors (as compared to true rumors) are more likely to go viral if they convey a higher proportion of terms associated with a positive sentiment. Further, false rumors are viral when embedding emotional words classified as trust, anticipation, or anger. All else being equal, false rumors conveying one standard deviation more positive sentiment have a 37.58% longer lifetime and reach 61.44% more users. Our findings offer insights into how true vs. false rumors spread and highlight the importance of managing emotions in social media content.

Highlights

  • False rumors on social media pose a significant threat to modern societies

  • For policy makers, understanding the spread of false content is necessary for developing mitigation strategies that directly target the viral effects of false content (e. g., educating users to exercise more critical thinking when confronted with emotional content)

  • We find that false rumors are characterized by cascades of larger size and longer lifetime

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Summary

Introduction

False rumors (often termed “fake news”) on social media pose a significant threat to modern societies. We analyze whether sentiment words, as well as different emotional words, in social media content explain differences in the spread of true vs false rumors. For this purpose, we collected N = 126,301 rumor cascades from Twitter, comprising more than 4.5 million retweets that have been fact-checked for veracity. We hypothesize that differences in the diffusion of true vs false rumors can be explained by the conveyed sentiment and basic emotions. Reliance on emotions further promotes belief in false i­nformation[31] This suggests that sentiment and emotions might offer a potential explanation for differences in the spreading dynamics of true vs false rumors; empirical evidence is lacking

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