A Comparative Analysis of the COVID-19 Infodemic in English and Chinese: Insights from Social Media Textual Data - Réseaux, Informatique, Systèmes de Confiance Access content directly
Journal Articles Frontiers in Public Health Year : 2023

A Comparative Analysis of the COVID-19 Infodemic in English and Chinese: Insights from Social Media Textual Data

Abstract

The COVID-19 infodemic, characterized by the rapid spread of misinformation and unverified claims related to the pandemic, presents a significant challenge. This paper presents a comparative analysis of the COVID-19 infodemic in the English and Chinese languages, utilizing textual data extracted from social media platforms. To ensure a balanced representation, two infodemic datasets were created by augmenting previously collected social media textual data. Through word frequency analysis, the thirty-five most frequently occurring infodemic words are identified, shedding light on prevalent discussions surrounding the infodemic. Moreover, topic clustering analysis uncovers thematic structures and provides a deeper understanding of primary topics within each language context. Additionally, sentiment analysis enables comprehension of the emotional tone associated with COVID-19 information on social media platforms in English and Chinese. This research contributes to a better understanding of the COVID-19 infodemic phenomenon and can guide the development of strategies to combat misinformation during public health crises across different languages.
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hal-04283683 , version 1 (14-11-2023)

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Jia Luo, Daiyun Peng, Lei Shi, Didier El Baz, Xinran Liu. A Comparative Analysis of the COVID-19 Infodemic in English and Chinese: Insights from Social Media Textual Data. Frontiers in Public Health, 2023, 11, ⟨10.3389/fpubh.2023.1281259⟩. ⟨hal-04283683⟩
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