Stigmatization in social media: Documenting and analyzing hate speech for COVID‐19 on Twitter

Abstract

As the COVID‐19 pandemic has unfolded, Hate Speech on social media about China and Chinese people has encouraged social stigmatization. For the historical and humanistic purposes, this history‐in‐the‐making needs to be archived and analyzed. Using the query “china+and+coronavirus” to scrape from the Twitter API, we have obtained 3,457,402 key tweets about China relating to COVID‐19. In this archive, in which about 40% of the tweets are from the U.S., we identify 25,467 Hate Speech occurrences and analyze them according to lexicon‐based emotions and demographics using machine learning and network methods. The results indicate that there are substantial associations between the amount of Hate Speech and demonstrations of sentiments, and state demographics factors. Sentiments of surprise and fear associated with poverty and unemployment rates are prominent. This digital archive and the related analyses are not simply historical, therefore. They play vital roles in raising public awareness and mitigating future crises. Consequently, we regard our research as a pilot study in methods of analysis that might be used by other researchers in various fields.

COVID-19: A Pandemic of Anti-Asian Cyberhate

“…The pandemic also prompted surges in global poverty and joblessness, the shuttering of countless businesses, mental health trauma, and food system disruptions resulting in new and worsening hunger crises (Usher et al, 2020;World Health Organization, 2020). Additionally, it inspired a wave of hate and hostility, especially towards those deemed "responsible" for the disease -namely, individuals of Asian descent, especially from China (Fan et al, 2020).…”

COVID - 19 ve Algoritmik Yanlılık: Küresel Bir Sağlık Krizinin Gölgesinde Algoritmik Yanlılığı Tartışmak

“…Çünkü dijital teknolojiler, bunların etkileri ve dijital teknolojiler ile birey arasındaki bilgi akışının anlamlandırılması sürecinde iletişim perspektifi önemli bir rol oynamaktadır. Örneğin, virüsle mücadele amacıyla sosyal mesafe ve tam kapanma gibi önlemler alınması sosyal ağları insanların bilgi kaynağı haline getirmiştir [6]. Sosyal ağların yankı odası yaratması ve algoritmaların kişilere ilgi alanlarıyla ilgili içerik önermesi bir kere yanlış bilgi alan kullanıcının bu döngüde kalmasına neden olabilmektedir [16].…”

Crisis Situations and Information Science. Selected Issues in the Context of the COVID-19 Pandemic

“…The platform is more and more frequently used as an official information channel by public institutions, such as governments or health public agencies. This is likely why tweets were the most often analyzed means of communication in information science scholarship (Chong, 2020;Dinh & Parulian, 2020;Fan et al, 2020;Karami & Anderson, 2020;Thelwall & Thelwall, 2020;Zheng et al, 2020).…”