Our team 'VINFO' (short for 'virulent information') focuses on the structure, spread and substance of SARS-CoV-2-related content. Our point of interest is the German-speaking "Querdenker" movement, especially its online journalism. We aim to analyze Querdenker online articles empirically, quantitatively and qualitatevily. Doing so, we will utilize different approaches, notably quantitative content analysis as well as qualitative content analysis.


Since about mid-2020, the main organizer of the protests against protective measures for COVID-19 pandemic in Germany has been a semi-organized group called Querdenken (lit. 'lateral thinking'), which was initially based in Stuttgart but soon started to organize rallies and demonstrations also in other cities.

The group is a non-centralized movement consisting of individuals from varied backgrounds, including anti-government protesters, supporters of various conspiracy theories, anti-vaxxers and members of the far-right. Previous research has shown that different actors of the ‘Querdenker’ movement have different motivations in their political support and they are often united by anti-scientific content, published and distributed online. These Querdenker online articles are the subject of our research.

Research Objectives

COVID-19-related misinformation can be created or adapted from the truth to attract the attention of target groups. In our project we analyze the out-of-context usage of scientific information that leads to misinformaion in the Querdenker community. We would like to understand this COVID-19-related misinformation in more detail in terms of its structure and spread, and to do so we closely look at Querdenker online articles.

Our research questions are:

  1. How is Covid-19 related misinformation in Querdenker online journalism expressed?
  2. To what extent can this information be traced back to information from scientific publications?
  3. What does the source-citation congruence look like?

First, we examine the Querdenker online articles in terms of their emotional tone and in terms of their scientific terminology. To do this, we will use language analysis tools such as LIWC (Linguistic Inquiry and Word Count) and a self-created dictionary about scientific terminology based on various science journals. We are happy to announce the completion of our dictionary. Here, we used a sample of around 3,000 articles from ZEIT Wissen, and 7,000 pages from Spektrum der Wissenschaft to obtain frequency tables for words which where then filtered by human raters in four different subcategories:

  1. scientific terms in life sciences
  2. scientific institutions & roles
  3. experimental language
  4. scientific terms in other natural sciences

In a second step, we will qualitatively examine a certain number of Querdenker online articles as a sample. We try to trace back the sources of the articles, respectively trace them back to specific scientific publications. Later on we will focus on similarities and differences between the Querdenker online articles and the original scientific publication or in other words, investigate how they align with each other.


  • Pia Gutsmiedl
  • Max Hampel
  • Seong-Min Jun
  • Cheng Pan
  • Valentin Pauli
  • Alexander Sobieska
  • Rosa Josephine Weidenspointner


  • Juna Zatsarnaja
  • Paul Sieber