Abstract

This study proposes a text analysis method for discovering patterns by which media narratives about Bats and SARS-CoV-2 are propagated in the media. Media narratives shape public perceptions and can lead to either correct/incorrect interpretations resulting in irreversible public actions. Early reports about the role of bats in the coronavirus pandemic led to the eradication of hibernating bats in China and the burning of roosting bats in Peru, despite the fact that there is no proof that humans can get SARS-CoV-2 from bats. These and other undocumented examples pose a major threat to biodiversity, as 80\% of bat species assessed by the International Union for the Conservation of Nature require conservation or research attention. Although well-reviewed academic studies frequently strive to rebut inaccurate perceptions about bats and viruses, stories that foster fear sometimes receive significant media attention. The method proposed by this study is the natural language processing method to underscore the various perspectives from three media platforms (GoogleNews, GoogleScholar, and Twitter platform), and Trend analysis across the various mediums.