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Journal Article

Neural topic modeling reveals German television’s climate change coverage

Authors
/persons/resource/tatjana.schirmag

Schirmag,  Tatjana
Potsdam Institute for Climate Impact Research;

/persons/resource/jakob.wedemeyer

Wedemeyer,  Jakob
Potsdam Institute for Climate Impact Research;

/persons/resource/Stechemesser

Stechemesser,  Annika
Potsdam Institute for Climate Impact Research;

/persons/resource/Leonie.Wenz

Wenz,  Leonie
Potsdam Institute for Climate Impact Research;
Submitting Corresponding Author, Potsdam Institute for Climate Impact Research;

External Ressource

https://zenodo.org/records/15333784
(Supplementary material)

Fulltext (public)

32306oa.pdf
(Publisher version), 2MB

Supplementary Material (public)
There is no public supplementary material available
Citation

Schirmag, T., Wedemeyer, J., Stechemesser, A., Wenz, L. (2025): Neural topic modeling reveals German television’s climate change coverage. - Communications Earth and Environment, 6, 441.
https://doi.org/10.1038/s43247-025-02402-1


Cite as: https://publications.pik-potsdam.de/pubman/item/item_32306
Abstract
The implementation and acceptance of climate policies depend on public perceptions of climate change. The media play a crucial role in informing the public discourse. While previous research has predominantly focused on written news, television remains the primary source of information globally. Here, we present an algorithm based on natural language processing techniques for identifying climate change coverage from subtitles of the leading German television news program, Tagesschau. Combining a dictionary approach with neural topic modeling, we classify the topics of over 28,000 news items (2015–2023). Our results show that climate change accounts for 4% of the total coverage, surpassed, for example, by sports coverage (9%). Acute crises, such as COVID-19, are covered more frequently and positioned more prominently. 80% of climate change coverage reports on climate policy, while only 10% covers climate impacts, like weather extremes. The latter tend to be covered in later news slots, indicating lower news value.