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Understanding patterns of COVID infodemic: A systematic and pragmatic approach to curb fake news.
Gupta, Ashish; Li, Han; Farnoush, Alireza; Jiang, Wenting.
  • Gupta A; Department of Systems & Technology, Raymond J. Harbert College of Business, Auburn University, Auburn, AL 36849, USA.
  • Li H; Department of Marketing, Information Systems, Information Assurance, and Operations Management, Anderson School of Management, University of New Mexico, Albuquerque, NM 87106, USA.
  • Farnoush A; Department of Industrial Engineering, Samuel Ginn College of Engineering, Auburn University, USA.
  • Jiang W; Department of Systems & Technology, Raymond J. Harbert College of Business, Auburn University, Auburn, AL 36849, USA.
J Bus Res ; 140: 670-683, 2022 Feb.
Article in English | MEDLINE | ID: covidwho-1517322
ABSTRACT
Amid the flood of fake news on Coronavirus disease of 2019 (COVID-19), now referred to as COVID-19 infodemic, it is critical to understand the nature and characteristics of COVID-19 infodemic since it not only results in altered individual perception and behavior shift such as irrational preventative actions but also presents imminent threat to the public safety and health. In this study, we build on First Amendment theory, integrate text and network analytics and deploy a three-pronged approach to develop a deeper understanding of COVID-19 infodemic. The first prong uses Latent Direchlet Allocation (LDA) to identify topics and key themes that emerge in COVID-19 fake and real news. The second prong compares and contrasts different emotions in fake and real news. The third prong uses network analytics to understand various network-oriented characteristics embedded in the COVID-19 real and fake news such as page rank algorithms, betweenness centrality, eccentricity and closeness centrality. This study carries important implications for building next generation trustworthy technology by providing strong guidance for the design and development of fake news detection and recommendation systems for coping with COVID-19 infodemic. Additionally, based on our findings, we provide actionable system focused guidelines for dealing with immediate and long-term threats from COVID-19 infodemic.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Systematic review/Meta Analysis Topics: Long Covid Language: English Journal: J Bus Res Year: 2022 Document Type: Article Affiliation country: J.jbusres.2021.11.032

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Systematic review/Meta Analysis Topics: Long Covid Language: English Journal: J Bus Res Year: 2022 Document Type: Article Affiliation country: J.jbusres.2021.11.032