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Swiss COVID-19 discourse framed misinformation differently across media

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Research area:Social SciencesSociology and Political SciencePublic Relations and Crisis Communication

What the study found

Swiss public discourse framed misinformation and disinformation differently across newspaper articles and social media during the COVID-19 pandemic. News media often linked these terms to public sentiment and to the tension between journalistic integrity and the spread of falsehoods, while social media more often centered on conspiracy theories, distrust in institutions, and grassroots mobilization.

Why the authors say this matters

The authors conclude that diverging narratives about misinformation and disinformation reflect broader societal tensions. They say that stronger journalistic integrity and resilience strategies, including information literacy approaches that empower the public, are critical to bridging divides and reducing polarization.

What the researchers tested

The researchers analyzed two datasets with a natural language processing pipeline, using lemmatization, co-occurrence analysis, and semantic network mapping. The datasets came from media articles retrieved via Factiva and social media posts collected via CrowdTangle.

What worked and what didn't

The analysis found significant differences in how the terms misinformation and disinformation were framed across the two datasets. News media emphasized the role of falsehoods in shaping public sentiment, while social media featured polarized narratives involving conspiracy theories and institutional distrust.

What to keep in mind

The abstract does not describe detailed limitations. The findings are specific to Swiss public discourse during the COVID-19 pandemic and to the two datasets analyzed.

Key points

  • News media and social media framed misinformation and disinformation differently in Swiss COVID-19 discourse.
  • News articles often discussed journalistic integrity and the amplification of falsehoods.
  • Social media discussions more often involved conspiracy theories, distrust in institutions, and grassroots mobilization.
  • The study used natural language processing, including lemmatization, co-occurrence analysis, and semantic network mapping.
  • The abstract says the divergent narratives reflect broader societal tensions.

Disclosure

Research title:
Swiss COVID-19 discourse framed misinformation differently across media
Authors:
Federico Germani, Giovanni Spitale, Franc Fritschi, Sonja Merten, Nikola Biller-Andorno
Institutions:
ZHAW Zurich University of Applied Sciences, University of Zurich, Institute for Biomedical Engineering, Swiss Tropical and Public Health Institute, University of Basel
Publication date:
2026-03-30
DOI:
10.2196/76441
OpenAlex record:
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AI provenance: This post was generated by OpenAI. The original authors did not write or review this post.

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