Surveillance of Twitter Data on COVID-19 Symptoms During the Omicron Variant Period: A Sentiment Analysis

This study underscores the potential of using social media, particularly tweet trends, for real-time analysis of COVID-19 infections and has demonstrated correlations with major symptoms. The degree of negative emotions expressed in tweets is valuable in predicting the emergence of new Omicron subvariants of COVID-19 and facilitating the provision of timely assistance to affected individuals.

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Publication Details

Journal
JMIR Formative Research
Published
2025-09-23
DOI
https://doi.org/10.2196/66237
Citations
2
Primary Topic
Misinformation and Its Impacts
Type
article
Field-Weighted Citation Impact
8.40
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article

Surveillance of Twitter Data on COVID-19 Symptoms During the Omicron Variant Period: A Sentiment Analysis

Ziyu Liu, Jian Huang, Chuxi Xiong, An-Ran Li et al.
2 citations
JMIR Formative Research
Misinformation and Its Impacts
8.40
article

Surveillance of Twitter Data on COVID-19 Symptoms During the Omicron Variant Period: A Sentiment Analysis

Ziyu Liu, Jian Huang, Chuxi Xiong, An-Ran Li, Yujie Ai, K Zhang, Zhaojin Guo, Taoran Liu, Wai‐Kit Ming, A. Li, Xinyu Zhou, Yittie Yi Ting Tse
article en
2 citations

Abstract

This study underscores the potential of using social media, particularly tweet trends, for real-time analysis of COVID-19 infections and has demonstrated correlations with major symptoms. The degree of negative emotions expressed in tweets is valuable in predicting the emergence of new Omicron subvariants of COVID-19 and facilitating the provision of timely assistance to affected individuals.

JMIR Formative ResearchVol. 9
University of Waterloo (CA), National University of Singapore (SG), City University of Hong Kong (HK), Peking University (CN), Government of Hong Kong (HK), Foundation for Human Potential (US), Hong Kong Jockey Club (HK), Peking University Third Hospital (CN), Bioinformatics Institute (SG), Hong Kong Shue Yan University (CN), University of Hong Kong (HK)
Openalex Percentile: Top 3%
Misinformation and Its Impacts
8.40
DOIOpen Access PDFOpenAlex
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Surveillance of Twitter Data on COVID-19 Symptoms During the Omicron Variant Period: A Sentiment Analysis — Ziyu Liu, Jian Huang, et al. · JMIR Formative Research (2025) | TGRS Research Map | TGRS