Developing Techniques to Support Technological Solutions to Disinformation by Analyzing Four Conspiracy Networks During COVID-19

Ahmed, Wasim; Onkal, Dilek; Das, Ronnie; Krishnan, Satish; Olan, Femi; Hardey, Mariann; Fenton, Alex

Abstract

Given the role of technology and social media during the COVID-19 pandemic, the aim of this article is to conduct a social network analysis of four COVID-19 conspiracy theories that were spread during the pandemic between March and June 2020. Specifically, in this article, we examine the 5G, Film Your Hospital, Expose Bill Gates, and the Plandemic Conspiracy theories. Identifying disinformation campaigns on social media and studying their tactics and composition is an essential step toward counteracting such campaigns. The current study draws upon data from the Twitter search application programming interface and uses social network analysis to examine patterns of disinformation that may be shared across social networks with sabotaging ramifications. The findings are used to generate the framework of disinformation seeding and information diffusion for understanding disinformation and the ideological nature of conspiracy networks that can support and inform future pandemic preparedness and counteracting disinformation. Furthermore, a Digital Mindfulness Toolbox is developed to support individuals and organizations with their information management and decision-making both in times of crisis and as strategic tools for potential crisis preparation.

Citation

Ahmed, W., Onkal, D., Das, R., Krishnan, S., Olan, F., Hardey, M., & Fenton, A. (in press). Developing Techniques to Support Technological Solutions to Disinformation by Analyzing Four Conspiracy Networks During COVID-19. IEEE Transactions on Engineering Management, https://doi.org/10.1109/TEM.2023.3273191

• Journal Article Type: Article
• Acceptance Date: May 1, 2023
• Online Publication Date: May 26, 2023
• Deposit Date: Nov 19, 2023
• Publicly Available Date: Nov 21, 2023
• Journal: IEEE Transactions on Engineering Management
• Print ISSN: 0018-9391
• Electronic ISSN: 1558-0040
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• DOI: https://doi.org/10.1109/TEM.2023.3273191
• Keywords: COVID-19; Data analytics; Fake news; Mindfulness; Misinformation; Twitter
• Public URL: https://hull-repository.worktribe.com/output/4447817
• Related Public URLs: https://durham-repository.worktribe.com/output/1173638/; http://hdl.handle.net/1893/35026