Hate Speech in a Telegram Conspiracy Channel During the First Year of the COVID-19 Pandemic. (November 2022)

• Record Type: Journal Article
• Authors: Vergani, Matteo; Martinez Arranz, Alfonso; Scrivens, Ryan; Orellana, Liliana
• Is Part Of: Social media + society. Volume 8:Number 4(2022)
• Publication Date: 2022-11
• Subjects: conspiracy theory -- online hate speech -- COVID-19 -- pandemic -- Telegram -- topic modeling -- automated text classification -- Sinophobia -- anti-journalist hate -- anti-doctors hate; Social media -- Periodicals; Social media -- Social aspects -- Periodicals; 302.231
• DOI: 10.1177/20563051221138758
• Languages: English
• ISSNs: 2056-3051

Abstract

Research has explored how the COVID-19 pandemic triggered a wave of conspiratorial thinking and online hate speech, but little is empirically known about how different phases of the pandemic are associated with hate speech against adversaries identified by online conspiracy communities. This study addresses this gap by combining observational methods with exploratory automated text analysis of content from an Italian-themed conspiracy channel on Telegram during the first year of the pandemic. We found that, before the first lockdown in early 2020, the primary target of hate was China, which was blamed for a new bioweapon. Yet over the course of 2020 and particularly after the beginning of the second lockdown, the primary targets became journalists and healthcare workers, who were blamed for exaggerating the threat of COVID-19. This study advances our understanding of the association between hate speech and a complex and protracted event like the COVID-19 pandemic, and it suggests that country-specific responses to the virus (e.g., lockdowns and re-openings) are associated with online hate speech against different adversaries depending on the social and political context.