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

• URL: http://arxiv.org/abs/2311.08001v1
• Date: Tue, 14 Nov 2023 08:55:11 GMT
• Title: A Comparative Analysis of the COVID-19 Infodemic in English and Chinese: Insights from Social Media Textual Data
• Authors: Jia Luo, Daiyun Peng, Lei Shi, Didier El Baz (LAAS-SARA), Xinran Liu
• Abstract summary: 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.
• Score: 2.641576480886427
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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