Pandemic Populism: Facebook Pages of Alternative News Media and the Corona Crisis -- A Computational Content Analysis
Svenja Boberg, Thorsten Quandt, Tim Schatto-Eckrodt, Lena Frischlich

TL;DR
This study uses computational content analysis to examine how alternative news media on Facebook during early COVID-19 spread ideological messages, conspiracy theories, and anti-systemic views, influencing societal perceptions.
Contribution
It provides an empirical analysis of alternative media's content during COVID-19, revealing their ideological consistency and role in pandemic populism through large-scale Facebook data.
Findings
Alternative media share consistent ideological patterns.
They predominantly spread critical and anti-systemic messages.
They contribute to societal distrust and conspiracy narratives.
Abstract
The COVID-19 pandemic has not only had severe political, economic, and societal effects, it has also affected media and communication systems in unprecedented ways. While traditional journalistic media has tried to adapt to the rapidly evolving situation, alternative news media on the Internet have given the events their own ideological spin. Such voices have been criticized for furthering societal confusion and spreading potentially dangerous "fake news" or conspiracy theories via social media and other online channels. The current study analyzes the factual basis of such fears in an initial computational content analysis of alternative news media's output on Facebook during the early Corona crisis, based on a large German data set from January to the second half of March 2020. Using computational content analysis, methods, reach, interactions, actors, and topics of the messages were…
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Taxonomy
TopicsMisinformation and Its Impacts · Social Media and Politics · Hate Speech and Cyberbullying Detection
