Racist Framing through Stigmatized Naming: A Topical and Geo-locational Analysis of #Chinavirus and #Chinesevirus on Twitter

During the COVID-19 pandemic, racists remarks accompanied by racist hashtags were disseminated via social media. Particularly, Asian Americans in the U.S. have been suffered from racism and xenophobia, resulting in physical violence and mental harassment in many cases. Despite the major function of the social media as an open-access platform for unedited and free speech for people with a diverse background, the global episodes of the soaring racism and xenophobia occurred in online public arenas reaffirmed that the platforms could be used for a nurturing ground of racism and xenophobia. This study examined the top influencers in the racist hashtag Twitter network and top shared neighboring hashtags with #Chinavirus or #Chinesevirus. We extracted topics from the racist hashtag Twitter network applying the state-of-the-art BERTopic modeling technique and conducted a geo-locational analysis of the participants of the network globally and by U.S. states. Trump was identified as the most influential actor in the #Chinavirus and #Chinesevirus Twitter network. This study confirmed previous literature that the political elite's public communication strategy to deviate the attention of the public suffered from the new disease and went through hardships under the epidemic crisis. Annual Meeting of the Association for Information Science & Technology | Oct. 29 – Nov. 3, 2021 | Salt Lake City, UT. Author(s) retain copyright, but ASIS&T receives an exclusive publication license.