| Literature DB >> 35250364 |
Padmali Rodrigo1, Emmanuel Ogiemwonyi Arakpogun1, Mai Chi Vu1, Femi Olan1, Elmira Djafarova1.
Abstract
This study explores the factors that influence the dissemination process of and public susceptibility to fake news amidst COVID-19. By adopting a qualitative approach that draws on 21 interviews with social media users from the standpoint of source credibility and construal level theories, our findings highlight motives of news sharers, platform features, and source credibility/relatedness as major factors influencing the dissemination of and public susceptibility to fake news. The paper further argues that public susceptibility to fake news can be mitigated by building an integrated approach that combines a tripartite strategy from an individual, institutional and platform level. For example, educating the public on digital resilience and enhancing awareness around source credibility can help individuals and institutions reflect on news authenticity and report fake news where possible. This study contributes to fake news literature by integrating concepts from information management, consumer behaviour, influencer marketing and mindfulness to propose a model to help authorities identify and understand the key factors that influence susceptibility to fake news during a public crisis such as COVID-19.Entities:
Keywords: COVID-19; Digital resilience; Fake news; Information management; Mindfulness
Year: 2022 PMID: 35250364 PMCID: PMC8889385 DOI: 10.1007/s10796-022-10258-5
Source DB: PubMed Journal: Inf Syst Front ISSN: 1387-3326 Impact factor: 6.191
Pilot Interview respondents’ Profiles
| Respondent | Age | Gender | Occupation |
|---|---|---|---|
| 1 | 38 | Female | Customer service executive |
| 2 | 36 | Male | Engineer |
| 3 | 34 | Female | Engineer |
| 4 | 40 | Male | Business owner |
| 5 | 28 | Female | Teacher |
Fig. 1Fake news thematic data map
Fig. 2A tripartite model for mitigating the impact of fake news
Timing of code development
| Interview number | Number of new codes identified |
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| 1 | 12 |
| 2 | 9 |
| 3 | 4 |
| 4 | 4 |
| 5 | 2 |
| 6 | 5 |
| 7 | 3 |
| 8 | 4 |
| 9 | 3 |
| 10 | 2 |
| 11 | 3 |
| 12 | 3 |
| 13 | 3 |
| 14 | 1 |
| 15 | 1 |
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Timing of code development versus code and meaning saturation (Example)
Illustrative sample quotes to support saturation codes and meaning
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