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Detecting sentiment dynamics and clusters of Twitter users for trending topics in COVID-19 pandemic

Author

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  • Md Shoaib Ahmed
  • Tanjim Taharat Aurpa
  • Md Musfique Anwar

Abstract

COVID-19 caused a significant public health crisis worldwide and triggered some other issues such as economic crisis, job cuts, mental anxiety, etc. This pandemic plies across the world and involves many people not only through the infection but also agitation, stress, fret, fear, repugnance, and poignancy. During this time, social media involvement and interaction increase dynamically and share one’s viewpoint and aspects under those mentioned health crises. From user-generated content on social media, we can analyze the public’s thoughts and sentiments on health status, concerns, panic, and awareness related to COVID-19, which can ultimately assist in developing health intervention strategies and design effective campaigns based on public perceptions. In this work, we scrutinize the users’ sentiment in different time intervals to assist in trending topics in Twitter on the COVID-19 tweets dataset. We also find out the sentimental clusters from the sentiment categories. With the help of comprehensive sentiment dynamics, we investigate different experimental results that exhibit different multifariousness in social media engagement and communication in the pandemic period.

Suggested Citation

  • Md Shoaib Ahmed & Tanjim Taharat Aurpa & Md Musfique Anwar, 2021. "Detecting sentiment dynamics and clusters of Twitter users for trending topics in COVID-19 pandemic," PLOS ONE, Public Library of Science, vol. 16(8), pages 1-20, August.
    • Handle: RePEc:plo:pone00:0253300
    DOI: 10.1371/journal.pone.0253300
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    Cited by:

    1. Fernando Arias & Ariel Guerra-Adames & Maytee Zambrano & Efraín Quintero-Guerra & Nathalia Tejedor-Flores, 2022. "Analyzing Spanish-Language Public Sentiment in the Context of a Pandemic and Social Unrest: The Panama Case," IJERPH, MDPI, vol. 19(16), pages 1-19, August.
    2. Jacqueline-Nathalie Harba & Gabriela Tigu & Adriana AnaMaria Davidescu, 2021. "Exploring Consumer Emotions in Pre-Pandemic and Pandemic Times. A Sentiment Analysis of Perceptions in the Fine-Dining Restaurant Industry in Bucharest, Romania," IJERPH, MDPI, vol. 18(24), pages 1-24, December.
    3. Gabriela Fernandez & Carol Maione & Harrison Yang & Karenina Zaballa & Norbert Bonnici & Jarai Carter & Brian H. Spitzberg & Chanwoo Jin & Ming-Hsiang Tsou, 2022. "Social Network Analysis of COVID-19 Sentiments: 10 Metropolitan Cities in Italy," IJERPH, MDPI, vol. 19(13), pages 1-31, June.

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