A deep dive into COVID-19-related messages on WhatsApp in Pakistan
Author | Javed, R. Tallal |
Author | Usama, Muhammad |
Author | Iqbal, Waleed |
Author | Qadir, Junaid |
Author | Tyson, Gareth |
Author | Castro, Ignacio |
Author | Garimella, Kiran |
Available date | 2023-07-13T05:40:53Z |
Publication Date | 2022 |
Publication Name | Social Network Analysis and Mining |
Resource | Scopus |
ISSN | 18695450 |
Abstract | The spread of COVID-19 and the lockdowns that followed led to an increase in activity on online social networks. This has resulted in users sharing unfiltered and unreliable information on social networks like WhatsApp, Twitter, Facebook, etc. In this work, we give an extended overview of how Pakistan's population used public WhatsApp groups for sharing information related to the pandemic. Our work is based on a major effort to annotate thousands of text and image-based messages. We explore how information propagates across WhatsApp and the user behavior around it. Specifically, we look at political polarization and its impact on how users from different political parties shared COVID-19-related content. We also try to understand information dissemination across different social networks-Twitter and WhatsApp-in Pakistan and find that there is no significant bot involvement in spreading misinformation about the pandemic. 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature. |
Sponsor | This work is supported by the UK EPSRC, under Grant EP/S033564/1 and facebook (Grant No. FY20PP013). |
Language | en |
Publisher | Springer |
Subject | Infodemic Misinformation Social computing |
Type | Article |
Issue Number | 1 |
Volume Number | 12 |
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Computer Science & Engineering [2288 items ]
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COVID-19 Research [818 items ]