Mechanisms of True and False Rumor Sharing in Social Media: Collective Intelligence or Herd Behavior?
MCML Authors
Stefan Feuerriegel
Prof. Dr.
Principal Investigator
Abstract
Stefan Feuerriegel
Prof. Dr.
Principal Investigator
Abstract
Social media platforms disseminate extensive volumes of online content, including true and, in particular, false rumors. Previous literature has studied the diffusion of offline rumors, yet more research is needed to understand the diffusion of online rumors. In this paper, we examine the role of lifetime and crowd effects in social media sharing behavior for true vs. false rumors. Based on 126,301 Twitter cascades, we find that the sharing behavior is characterized by lifetime and crowd effects that explain differences in the spread of true as opposed to false rumors. All else equal, we find that a longer lifetime is associated with less sharing activities, yet the reduction in sharing is larger for false than for true rumors. Hence, lifetime is an important determinant explaining why false rumors die out. Furthermore, we find that the spread of false rumors is characterized by herding tendencies (rather than collective intelligence), whereby the spread of false rumors becomes proliferated at a larger cascade depth. These findings explain differences in the diffusion dynamics of true and false rumors and further offer practical implications for social media platforms.
inproceedings
CHI 2023
Conference on Human Factors in Computing Systems. Hamburg, Germany, Apr 23-28, 2023.
Authors
N. Pröllochs • S. FeuerriegelLinks
DOIResearch Area
BibTeXKey: PF23