Mourad, Azzam, Srour, Ali, Harmanani, Haidar, Jenainati, Cathia and Arafeh, Mohamad (2020) Critical impact of social networks infodemic on defeating coronavirus COVID-19 pandemic: Twitter-based study and research directions. IEEE Transactions on Network and Service Management, 17 (4). pp. 2145-2155. doi:10.1109/TNSM.2020.3031034
Full text not available from this repository.Abstract
News creation and consumption has been changing since the advent of social media. An estimated 2.95 billion people in 2019 used social media worldwide. The widespread of the Coronavirus COVID-19 resulted with a tsunami of social media. Most platforms were used to transmit relevant news, guidelines and precautions to people. According to WHO, uncontrolled conspiracy theories and propaganda are spreading faster than the COVID-19 pandemic itself, creating an infodemic and thus causing psychological panic, misleading medical advises, and economic disruption. Accordingly, discussions have been initiated with the objective of moderating all COVID-19's communications, except those initiated from trusted sources such as the WHO and authorized governmental entities. This article presents a large-scale study based on data mined from Twitter. Extensive analysis has been performed on approximately one million COVID-19 related tweets collected over a period of two months. Furthermore, the profiles of 288,000 users were analyzed including unique users' profiles, meta-data and tweets' context. The study noted various interesting conclusions including the critical impact in term of reach level of the (1) exploitation of the COVID-19 crisis to redirect readers to irrelevant topics and (2) widespread of unauthentic medical precautions and information. Further data analysis revealed the importance of using social networks in a global pandemic crisis by relying on credible users with variety of occupations, content developers and influencers in specific fields. In this context, several insights and findings have been provided while elaborating computing and non-computing implications and research directions for potential solutions and social networks management strategies during crisis periods.
Item Type: | Article |
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Article Type: | Article |
Uncontrolled Keywords: | Coronavirus; COVID-19; Pandemic; Infodemic; Misinformation; Misleading information; Social networks; Social networks management; Defeating coronavirus; Data analytics |
Subjects: | Q Science > QA Mathematics > QA76 Computer software |
Divisions: | Schools and Research Institutes > School of Business, Computing and Social Sciences |
Research Priority Areas: | Applied Business & Technology |
Depositing User: | Rhiannon Goodland |
Date Deposited: | 24 Oct 2023 13:59 |
Last Modified: | 24 Oct 2023 13:59 |
URI: | https://eprints.glos.ac.uk/id/eprint/13353 |
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