Why people spread rumors on social media: developing and validating a multi-attribute model of online rumor dissemination

Abstract

PurposeDealing with online rumors or fake information on social media is growing in importance. Most academic research on online rumors has approached the issue from a quantitative modeling perspective. Less attention has been paid to the psychological mechanisms accounting for online rumor transmission behavior on the individual level. Drawing from the theory of stimulus–organism–response, this study aims to explore the nature of online rumors and investigate how the informational characteristics of online rumors are processed through the mediation of psychological variables to promote online rumor forwarding.Design/methodology/approachAn experimental approach to this issue was taken; the researchers investigated how the informational characteristics of online rumors and the psychological mediators promote online rumor transmission.FindingsFour information characteristics (sense-making, funniness, dreadfulness and personal relevance) and three psychological motivators (fact-finding, relationship enhancement and self-enhancement) promote online rumor-forwarding behavior.Originality/valueBecause any online rumor transmitted on social media can go viral, companies may eventually encounter social media-driven crises. Thus, understanding what drives rumor-forwarding behavior can help marketers mitigate and counter online rumors.

The application of emotions, sharing motivations, and psychological distance in examining the intention to share COVID-19-related fake news

“…Various motivations—romantic, information seeking, attention seeking (status attainment), entertainment, relation enhancement, self-enhancement, and socializing—have been identified (Lee and Ma, 2012; Goh et al. , 2009; Shen et al. , 2021).…”

“…Several studies have referred to the uses and gratifications theory to interpret social media-based information-sharing behavior (Thompson et al, 2020). Various motivationsromantic, information seeking, attention seeking (status attainment), entertainment, relation enhancement, self-enhancement, and socializing-have been identified (Lee and Ma, 2012;Goh et al, 2009;Shen et al, 2021). Talwar et al (2019) showed that social media fatigue, social comparison, self-disclosure, fear of missing out, and online trust influence fake news sharing intention.…”

Cross-social networks analysis: building me-edge centered BUNet dataset based on implicit bridge users

“…In fact, OSNs have been exploited for spreading fake news and rumors (Zubiaga et al. , 2018; Shelke and Attar, 2019; Shen et al. , 2021).…”

“…The study of information diffusion (Kim et al, 2018;Bhowmick, 2020;Kumar et al, 2021) has been investigated more on intra than on inter-social networks as it is easy to identify connections used to transport data on intra-social networks. In fact, OSNs have been exploited for spreading fake news and rumors (Zubiaga et al, 2018;Shelke and Attar, 2019;Shen et al, 2021). Zubiaga et al (2018) focused on the detection of the spread of false information on one social network but it seems that there is just few works OIR 47,1 (Farahbakhsh et al, 2016;Keikha et al, 2020) tackling the spread of information across multiple OSNs, due to the lack of cross-social networks datasets.…”

Text Mining based Rumor Detection on Twitter data

“…The flexibility and simplicity with which information on social media platforms may be disseminated stimulate the spread of information across the network, regardless of its veracity. This sort of disinformation is typically disseminated in the event of an exclusive piece of news [34,35]. As a result of unconfirmed information, such information, sometimes referred to as rumors, has the potential to do catastrophic damage.…”