Rumor Diffusion on Social Media During the COVID-19 Pandemic

• Applicant: Professor Dr. Nicolas Pröllochs
• Subject Area: Management and Marketing
• Term: since 2021
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 455368471

Social media platforms disseminate extensive volumes of online content, yet oftentimes also deceptive content in the form of false rumors. The latter becomes particularly evident in the current COVID-19 pandemic in which the verdicts of fact-checking organizations (e.g., politifact.com, snopes.com) suggest that social media is rife with COVID-19-related false rumors. Given that exposure to false rumors frequently manifests in offline consequences, there is an urgency to understand how rumors diffuse on social media in the context of COVID-19. However, such an understanding is largely absent in the current crisis situation. Therefore, this project aims to holistically analyze the spread of true and false rumors on social media during the COVID-19 pandemic. Specifically, we will analyze rumor cascades propagating on Twitter from two large-scale data sources: (i) rumor cascades that have been expert fact-checked by three fact-checking organizations; (ii) rumor cascades that have been community fact-checked on Twitter’s Birdwatch platform. Based on these datasets, we will analyze how the veracity of a rumor is associated with differences in users’ sharing propensity. Moreover, the proposed research project will investigate additional internal and external factors that may affect users’ sharing behavior of true and false rumors (e.g., surging/declining case COVID-19 case numbers, the speed of fact-checking, COVID-19-specific sub-topics). As a further contribution, we will also analyze how the believability and harmfulness of rumors are associated with their spread. The overarching goal of this project is to enhance our understanding of how users react to rumors on social media during the COVID-19 pandemic. As an extension, we will evaluate whether the findings from this project can be harnessed in machine learning models to predict the spread of rumors on social media. Based on the generated insights, the project will derive important implications for social media platforms and policymakers.

• DFG Programme: Research Grants