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Misinformation debunking and cross-platform information sharing through Twitter during Hurricanes Harvey and Irma: a case study on shelters and ID checks

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Abstract

As the internet and social media continue to become increasingly used for sharing breaking news and important updates, it is with great motivation to study the behaviors of online users during crisis events. One of the biggest issues with obtaining information online is the veracity of such content. Given this vulnerability, misinformation becomes a very dangerous and real threat when spread online. This study investigates misinformation debunking efforts and fills the research gap on cross-platform information sharing when misinformation is spread during disasters. The false rumor “immigration status is checked at shelters” spread in both Hurricane Harvey and Hurricane Irma in 2017 and was analyzed in this paper based on a collection of 12,900 tweets. By studying the rumor control efforts made by thousands of accounts, we found that Twitter users respond and interact the most with tweets from verified Twitter accounts, and especially government organizations. Results on sourcing analysis show that the majority of Twitter users who utilize URLs in their postings are employing the information in the URLs to help debunk the false rumor. The most frequently cited information comes from news agencies when analyzing both URLs and domains. This paper provides novel insights into rumor control efforts made through social media during natural disasters and also the information sourcing and sharing behaviors that users exhibit during the debunking of false rumors.

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Acknowledgements

This research was partially supported by the National Science Foundation (NSF) under Award Nos. 1762807 and 1760586. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. We also thank two referees for providing constructive comments.

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  1. Department of Industrial and Systems Engineering, University at Buffalo, Buffalo, USA

    Kyle Hunt, Bairong Wang & Jun Zhuang

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  1. Kyle Hunt
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  2. Bairong Wang
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  3. Jun Zhuang
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Correspondence to Jun Zhuang.

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Appendix 1: Search criteria used for tweet collection

Appendix 1: Search criteria used for tweet collection

See Table 6.

Table 6 Search criteria used to collect all tweets and retweets in both cases
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1.1 Appendix 2: Data coding rubric

See Table 7.

Table 7 Coding rubric used to define the different categories
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Hunt, K., Wang, B. & Zhuang, J. Misinformation debunking and cross-platform information sharing through Twitter during Hurricanes Harvey and Irma: a case study on shelters and ID checks. Nat Hazards 103, 861–883 (2020). https://doi.org/10.1007/s11069-020-04016-6

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