Automated measurement of attitudes towards social distancing using social media: A COVID-19 case study

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Kayes, ASM
Islam, Md Saiful
Watters, Paul A
Ng, Alex
Kayesh, Humayun
Griffith University Author(s)
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2020
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Abstract

The COVID-19 outbreak has focused attention on the use of social distancing as the primary defence against community infection. Forcing social animals to maintain physical distance has presented significant challenges for health authorities and law enforcement. Anecdotal media reports suggest widespread dissatisfaction with social distancing as a policy, yet there is little prior work aimed at measuring community acceptance of social distancing. In this paper, we propose a new approach to measuring attitudes towards social distancing by using social media and sentiment analysis. Over a four-month period, we found that 82.5 percent of tweets were in favour of social distancing. The results indicate a widespread acceptance of social distancing in a selected community. We examine options for estimating the optimal (minimal) social distance required at scale, and the implications for securing widespread community support and for appropriate crisis management during emergency health events.

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First Monday

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25

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11

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© 2020, A.S.M. Kayes, Md. Saiful Islam, Paul A. Watters, Alex Ng, and Humayun Kayesh. All Rights Reserved. his is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Deep learning

Artificial intelligence not elsewhere classified

Social theory

Information systems

Library and information studies

Communication and media studies

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Kayes, ASM; Islam, MS; Watters, PA; Ng, A; Kayesh, H, Automated measurement of attitudes towards social distancing using social media: A COVID-19 case study, First Monday, 25 (11)

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