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

Abstract

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.

The impact of the COVID-19 pandemic on the creative industries: A literature review and future research agenda

“…The reviewed literature on the impact of the COVID-19 pandemic on the creative industries included both qualitative (e.g., Agostino et al, 2020 , Davies, 2020 , Temiz and Salelkar, 2020 ) and quantitative methods (regression analysis, Monte Carlo simulation). However, there are too few quantitative papers to examine this area for research ( Bae et al, 2021 , Apuke and Omar, 2021 , Koulouris et al, 2020 , Urbaczewski and Lee, 2020 ). Future studies could consider developing more sophisticated quantitative-based and mixed-method approaches when examining the social and economic impact of the pandemic on the creative industries.…”

“…Websites and social media played an important role in the digital safety net while lockdown restrictions were in place and physical contact between people was limited (Connected Commerce Council, 2020 , Landi et al, 2021 , Marabelli et al, 2021 ). Businesses increased their use of remote services via social media tools and platforms (e.g., Facebook, Instagram, LinkedIn, Tik-Tok) ( Bae et al, 2021 , Marabelli et al, 2021 ; Cifuentes-Faura, 2020; Kaya, 2020 , Ferrara et al, 2020 ).…”

“…Recent studies have investigated the “infodemics” which appeared during the early stages of the COVID-19 pandemic ( Apuke and Omar, 2021 , Bae et al, 2021 ; Cifuentes-Faura, 2020; Ferrara et al, 2020 , Greenspan and Loftus, 2021 , Kumar and Sharma, 2021 , Zeng and Chan, 2021 ). “Infodemics” refers here to the dissemination of fake news, especially via social media.…”

Social Media Use, Self-Efficacy, Perceived Threat, and Preventive Behavior in Times of COVID-19: Results of a Cross-Sectional Study in Pakistan

“…The COVID-19 pandemic has permanently altered the global landscape. The crippling consequences of the lockdown have been felt in all spheres of life (Bae et al, 2021), including a crumbling health system (Miller et al, 2020;Mahmood et al, 2021), panic buying (Ahmad and Murad, 2020;Arafat et al, 2020), a severe and difficult-to-resolve economic and labor crisis (Sukharev, 2020), high levels of distress (Cullen et al, 2020), and so on. Both the short-term and long-term effects of the COVID-19 pandemic have influenced how people view and represent current events and future scenarios, including adherence to preventive behavior (Liu, 2021).…”

#StayHome or #Marathon? Social Media Enhanced Pandemic Surveillance on Spatial-temporal Dynamic Graphs

“…Qin et al [63] employ the search index of Baidu search engine to serve as a pandemic early predictor. Bae et al [5] leverage the social effect of media information to strengthen the compartment model for pandemic prediction. However, this study solely takes into consideration the social effects of the media to users' normal life while our method curate every tweet and detect significant social events to enhance the pandemic prediction.…”