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Spotting Flares: The Vital Signs of the Viral Spread of Tweets Made During Communal Incidents

Published:16 November 2022Publication History
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Abstract

With the increasing use of Twitter for encouraging users to instigate violent behavior with hate and racial content, it becomes necessary to investigate the uniqueness in the dynamics of the spread of tweets made during violent communal incidents and the challenges they pose in early identification of potential viral content. In this article, we study the spread of the tweets made during several violent communal incidents along four major dimensions — the underlying follower network of the users, their structural and engagement characteristics, the cascades, and the cognitive aspects of the content, each of which plays a vital role in the spread of content. Using large public and collected data, we compare these features with tweets related to other subjects from several major domains, such as non-violent political events, celebrities, and technology, that contribute to a large fraction of the viral content over Twitter. We discover that while the spread of cascades and the users involved may provide strong early evidence of the viral content for several domains, the early phases of the spread of viral tweets related to violent communal incidents are characterized by cascades with protracted growth involving fringe or low-importance users, which would possibly make early prediction difficult. Our findings indicate that an interplay of certain network and cascade properties, together with the cognitive characteristics of tweets and the behavioral patterns of the engaging users, may provide stronger early indicators of the virality of this content.

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        cover image ACM Transactions on the Web
        ACM Transactions on the Web  Volume 16, Issue 4
        November 2022
        165 pages
        ISSN:1559-1131
        EISSN:1559-114X
        DOI:10.1145/3571715
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        Publication History

        • Published: 16 November 2022
        • Online AM: 13 September 2022
        • Accepted: 30 June 2022
        • Revised: 3 June 2022
        • Received: 24 April 2021
        Published in tweb Volume 16, Issue 4

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