Methodology to Compare Twitter Reaction Trends between Disinformation Communities, to COVID related Campaign Events at Different Geospatial Granularities

Debraj De, Gautam Thakur, Drahomira Herrmannova, Carter Christopher

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

With still ongoing COVID pandemic, there is an immediate need for a deeper understanding of how Twitter discussions (or chatters) in disinformation spreading communities get triggered. More specifically, the value is in monitoring how such trigger events in Twitter discussion do align with the timelines of relevant influencing events in the society (indicated in this work as campaign events). For campaign events in regards to COVID pandemic, we consider both NPI (Nonpharmaceutical Interventions) campaigns and disinformation spreading campaigns together. In this short paper we have presented a novel methodology to quantify, compare and relate two Twitter disinformation communities, in terms of their reaction patterns to the timelines of major campaign events. We have also analyzed these campaigns at their three geospatial granularity contexts: local county, state, and country/ federal. We have conducted a novel dataset collection on campaigns (NPI + Disinformation) at these different geospatial granularities. Then, with collected dataset on Twitter disinformation communities, we have performed a case study to validate our proposed methodology.

Original languageEnglish
Title of host publicationWWW 2022 - Companion Proceedings of the Web Conference 2022
PublisherAssociation for Computing Machinery, Inc
Pages458-463
Number of pages6
ISBN (Electronic)9781450391306
DOIs
StatePublished - Apr 25 2022
Event31st ACM Web Conference, WWW 2022 - Virtual, Online, France
Duration: Apr 25 2022 → …

Publication series

NameWWW 2022 - Companion Proceedings of the Web Conference 2022

Conference

Conference31st ACM Web Conference, WWW 2022
Country/TerritoryFrance
CityVirtual, Online
Period04/25/22 → …

Funding

This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (https://energy.gov/downloads/doe-public-access-plan).

FundersFunder number
U.S. Department of Energy

    Keywords

    • COVID-19 pandemic
    • Disinformation
    • NPI (Nonpharmaceutical Interventions)
    • Twitter data

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