COVID-19 pandemic and information diffusion analysis on Twitter.

ABSTRACT: The COVID-19 pandemic has impacted all aspects of our lives, including the information spread on social media. Prior literature has found that information diffusion dynamics on social networks mirror that of a virus, but applying the epidemic Susceptible-Infected-Removed model (SIR) model to examine how information spread is not sufficient to claim that information spreads like a virus. In this study, we explore whether there are similarities in the simulated SIR model (SIRsim), observed SIR model based on actual COVID-19 cases (SIRemp), and observed information cascades on Twitter about the virus (INFOcas) by using network analysis and diffusion modeling. We propose three primary research questions: (a) What are the diffusion patterns of COVID-19 virus spread, based o

SUBMITTER: Dinh L 

PROVIDER: S-EPMC7645904 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature