Emotions explain differences in the diffusion of true vs. false social media rumors

Pröllochs, Nicolas; Bär, Dominik und Feuerriegel, Stefan (2021): Emotions explain differences in the diffusion of true vs. false social media rumors. In: Scientific Reports, Bd. 11, Nr. 1, 22721

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 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.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Betriebswirtschaft
• Themengebiete: 300 Sozialwissenschaften > 330 Wirtschaft
• ISSN: 2045-2322
• Sprache: Englisch