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 30 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 a

SUBMITTER: Luo J 

PROVIDER: S-EPMC10686410 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature