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A Tempest in a Teacup? Analyzing Firestorms on Twitter

Authors:

Momin M. Malik,

Jürgen PfefferAuthors Info & Claims

ASONAM '15: Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015

Pages 17 - 24

https://doi.org/10.1145/2808797.2808828

Published: 25 August 2015 Publication History

Abstract

'Firestorms,' sudden bursts of negative attention in cases of controversy and outrage, are seemingly widespread on Twitter and are an increasing source of fascination and anxiety in the corporate, governmental, and public spheres. Using media mentions, we collect 80 candidate events from January 2011 to September 2014 that we would term 'firestorms.' Using data from the Twitter decahose (or gardenhose), a 10% random sample of all tweets, we describe the size and longevity of these firestorms. We take two firestorm exemplars, #myNYPD and #CancelColbert, as case studies to describe more fully. Then, taking the 20 firestorms with the most tweets, we look at the change in mention networks of participants over the course of the firestorm as one method of testing for possible impacts of firestorms. We find that the mention networks before and after the firestorms are more similar to each other than to those of the firestorms, suggesting that firestorms neither emerge from existing networks, nor do they result in lasting changes to social structure. To verify this, we randomly sample users and generate mention networks for baseline comparison, and find that the firestorms are not associated with a greater than random amount of change in mention networks.

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cover image ACM Conferences

ASONAM '15: Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015

August 2015

835 pages

ISBN:9781450338547

DOI:10.1145/2808797

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 25 August 2015

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Basak RSural SGhosh S(2024)Progress Tracking and Responding to Online Public Shaming Events on TwitterIEEE Transactions on Computational Social Systems10.1109/TCSS.2023.329513111:2(2091-2104)Online publication date: Apr-2024
https://doi.org/10.1109/TCSS.2023.3295131
Brannon WRoy D(2024)The speed of news in Twitter (X) versus radioScientific Reports10.1038/s41598-024-61921-714:1Online publication date: 24-May-2024
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