A Social Network Information Propagation Model Considering Different Types of Social Relationships

Zhao, Chunjiang; Zhang, Zhiyong; Li, Hanman; Zhao, Shiyang

doi:10.1007/978-3-319-01796-9_29

Cited by 1 publication

(1 citation statement)

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“…However, in later stages, efforts to stabilise the situation could be interpreted as increasing the positive function of social media as the number of infections increased, along with COVID-19 testing and the social threat of exposure to COVID-19. Particularly, the positive function and negative function of social motivation could be interpreted as sources of protection and propagation, respectively, in a hazardous situation (Zhao et al, 2014). During the early stages, slandering and hate speech were the main focus, but as time went by, a sense of shared responsibility became a functional element.…”

Section: Theoretical Implicationsmentioning

confidence: 99%

Accounting for social media effects to improve the accuracy of infection models: combatting the COVID-19 pandemic and infodemic

Bae

Sung

Kwon

2021

European Journal of Information Systems

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During the COVID-19 pandemic, social media platfforms such as Twitter, Facebook, etc. have played an important role in conveying information, both accurate and inaccurate, thereby creating mass confusion. As the response to COVID-19 has reduced face-to-face contact, communication via social media has increased. Evidence shows that social media affects disease (non-)prevention through the (im)proper distribution of information, and distorts the predictive accuracy of infection models, including legacy Susceptible-Exposed-Infectious-Recovered (SEIR) models. Our adjusted SEIR model reflects the effectiveness of information disseminated through social media by accounting for dimensions of social/informational motivation based on social learning/use and gratification theories, and uses Monte Carlo methodology and computational algorithms to predict effects of social media on the spread of COVID-19 (N = 2,095 cases). The results suggest that social media utilisation measures should be incorporated into SEIR models to improve forecasts of COVID-19 infections. Utilising IS to analyse the spread of digital information via social media platforms can inform efforts to combat the pandemic and infodemic. Agencies responsible for infection and disease control, policy makers, businesses, institutions and educators must accurately monitor infection rates to appropriately allocate funding and human resources and develop effective disease prevention marketing campaigns.

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Section: Theoretical Implicationsmentioning

confidence: 99%