GECO: A Twitter Dataset of COVID-19 Misinformation and Conspiracy Theories Related to the Berlin Parliament and Washington Capitol Riots


  • Stefan Brenner Stuttgart Media University
  • Daniel Thilo Schroeder Simula Research Laoratory, SINTEF, Oslo Metropolitan University
  • Johannes Langguth Simula Research Laboratory, BI Norwegian Business School


Misinformation, Conspiracy Theories, Twitter, Human-annotated data


On August 29, 2020, a precursor to the widely known January 6 United States Capitol attack in Washington D.C., USA, occurred in Berlin, Germany, where a group of protesters participating in a demonstration against COVID-19 pandemic measures attempted to storm the German parliament in Berlin. While the event in Berlin was less dramatic than January 6 of 2021 in the US - the protesters were repelled by the police, and no serious damage or injuries were reported - in both cases, mobilization through conspiracy theories on social media is widely considered a significant factor leading to both events.

In this paper, in order to study such social media content, we present an analysis based on a manually labeled dataset sampled from a large set of COVID-19 related tweets in temporal proximity to the event in Berlin. Moreover, we provide an analysis that is based on a set of tweets following the January 6 United States Capitol event for comparison. The labels distinguish eight different classes of conspiracy theories, as well as other misinformation. This allows for studying the prevalence of different misinformation narratives around events of note. In total
23,417 tweets were labeled manually.

The purpose of this dataset analysis is to allow further study of the phenomena, as well as training of machine learning systems with the purpose of detecting conspiracy theory content.


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