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dc.contributor.authorJaved, R. Tallal
dc.contributor.authorUsama, Muhammad
dc.contributor.authorIqbal, Waleed
dc.contributor.authorQadir, Junaid
dc.contributor.authorTyson, Gareth
dc.contributor.authorCastro, Ignacio
dc.contributor.authorGarimella, Kiran
dc.date.accessioned2022-05-09T20:53:30Z
dc.date.available2021-11-15T12:56:16Z
dc.date.available2022-05-09T20:53:30Z
dc.date.issued2021-11
dc.date.submitted2021-10
dc.identifier.issn1869-5450
dc.identifier.issn1869-5469
dc.identifier.urihttps://hdl.handle.net/1721.1/138127.2
dc.description.abstractAbstract 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.en_US
dc.publisherSpringer Science and Business Media LLCen_US
dc.relation.isversionofhttps://doi.org/10.1007/s13278-021-00833-0en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceSpringer Viennaen_US
dc.titleA deep dive into COVID-19-related messages on WhatsApp in Pakistanen_US
dc.typeArticleen_US
dc.identifier.citationSocial Network Analysis and Mining. 2021 Nov 15;12(1):5en_US
dc.contributor.departmentMassachusetts Institute of Technology. Institute for Data, Systems, and Society
dc.relation.journalSocial Network Analysis and Miningen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2021-11-15T04:08:46Z
dc.language.rfc3066en
dc.rights.holderThe Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature
dspace.embargo.termsY
dspace.date.submission2021-11-15T04:08:46Z
mit.journal.volume12en_US
mit.journal.issue1en_US
mit.licensePUBLISHER_POLICY
mit.metadata.statusAuthority Work Neededen_US


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