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138127.2 |
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|a Javed, R. Tallal
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|a Usama, Muhammad
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|a Iqbal, Waleed
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|a Qadir, Junaid
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|a Tyson, Gareth
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|a Castro, Ignacio
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|a Garimella, Kiran
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|a A deep dive into COVID-19-related messages on WhatsApp in Pakistan
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|b Springer Science and Business Media LLC,
|c 2022-05-09T20:53:30Z.
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|z Get fulltext
|u https://hdl.handle.net/1721.1/138127.2
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|a 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.
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|a Article
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|t Social Network Analysis and Mining
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