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Social Media User Behavior and Emotions during Crisis Events

Author

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  • Mingyun Gu

    (College of Economics and Management, China University of Geosciences, Wuhan 430074, China
    Research Center for Digital Business Management, China University of Geosciences, Wuhan 430074, China)

  • Haixiang Guo

    (College of Economics and Management, China University of Geosciences, Wuhan 430074, China
    Research Center for Digital Business Management, China University of Geosciences, Wuhan 430074, China
    Mineral Resource Strategy and Policy Research Center, China University of Geosciences, Wuhan 430074, China)

  • Jun Zhuang

    (Department of Industrial and Systems Engineering, School of Engineering and Applied Sciences, University at Buffalo, SUNY 317 Bell Hall, Buffalo, NY 14260, USA)

  • Yufei Du

    (College of Economics and Management, China University of Geosciences, Wuhan 430074, China)

  • Lijin Qian

    (College of Economics and Management, China University of Geosciences, Wuhan 430074, China)

Abstract

The wide availability of smart mobile devices and Web 2.0 services has allowed people to easily access news, spread information, and express their opinions and emotions using various social media platforms. However, because of the ease of joining these sites, people also use them to spread rumors and vent their emotions, with the social platforms often playing a facilitation role. This paper collected more than 190,000 messages published on the Chinese Sina-Weibo platform to examine social media user behaviors and emotions during an emergency, with a particular research focus on the “Dr. Li Wenliang” reports associated with the COVID-19 epidemic in China. The verified accounts were found to have the strongest interactions with users, and the sentiment analysis revealed that the news from government agencies had a positive user effect and the national media and trusted experts were more favored by users in an emergency. This research provides a new perspective on trust and the use of social media platforms in crises, and therefore offers some guidance to government agencies.

Suggested Citation

  • Mingyun Gu & Haixiang Guo & Jun Zhuang & Yufei Du & Lijin Qian, 2022. "Social Media User Behavior and Emotions during Crisis Events," IJERPH, MDPI, vol. 19(9), pages 1-21, April.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:9:p:5197-:d:801487
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    References listed on IDEAS

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    Cited by:

    1. Hongzhou Shen & Yue Ju & Zhijing Zhu, 2023. "Extracting Useful Emergency Information from Social Media: A Method Integrating Machine Learning and Rule-Based Classification," IJERPH, MDPI, vol. 20(3), pages 1-20, January.
    2. Shangyi Yan & Jingya Wang & Zhiqiang Song, 2022. "Microblog Sentiment Analysis Based on Dynamic Character-Level and Word-Level Features and Multi-Head Self-Attention Pooling," Future Internet, MDPI, vol. 14(8), pages 1-19, July.

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