cs.IRAug 18, 2026

Global Crises and National Policies: A Large Scale Analysis of Political Content in German Language Online Media

Authors: Yara Döring, Felix Bießmann

Organizations: Berliner Hochschule für Technik · Einstein Center Digital Future, Berlin

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Abstract

Today most media content is consumed based on algorithmic recommendations. Evidence suggests that this can lead to politically biased media consumption patterns. Automated extraction of political agendas from texts can reveal and analyze political biases in online media -- and thus help fostering politically unbiased media consumption. Here we employ modern political text analysis methods demonstrating the potential of automated fine-grained political bias analysis in online media. We conduct an analysis of political content in German language online media during the period 2019--2022, encompassing several million articles and tweets covering events with profound societal impact globally and nationally, the COVID-19 pandemic and the beginning of the war in Ukraine. Our analysis identifies thematic similarity between national (German and Swiss) reporting, particularly for categories driven by international events. We also find divergences emerging in domestically influenced categories, reflecting differences in national policies and institutional structures. A comparison of newspaper and Twitter discourse reveals that both media converge around a shared core during the pandemic, yet differ in intensity and temporal dynamics. Newspapers exhibit more stable political content, while Twitter reacts through short-lived event-driven spikes. These findings indicate that international crises act as a powerful synchronizing force on political content in classical media, temporarily overriding both national and media-form differences. Our automated political analysis empowers citizens by rendering political agendas in online media transparent. This transparency also enables media outlets to bridge the gap between algorithm-driven echo chambers and a more informed, balanced public discourse.

Figures & tables

YearGermanySwitzerland
2019489,1622,824
2020655,01231,705
2021784,27230,675
20221,195,60032,729
Total3,124,04697,933
Table 1: Number of crawled news articles by year and country.
Figure 1: Distribution of articles across newspapers in Germany (DE) and Switzerland (CH). The dataset is dominated by German outlets, with only three Swiss newspapers included: Tages-Anzeiger, Schweizer Radio und Fernsehen, and Neue Zürcher Zeitung (NZZ).
Figure 2: Longitudinal trends in thematic domain shares across newspapers and Twitter across pre-pandemic, pandemic core, and post-pandemic phases. Newspapers exhibit relatively stable distributions throughout, while Twitter shows considerably higher volatility, particularly during the pandemic core phase, where several domains spike sharply before subsiding.
Figure 3: Distribution of thematic domains in newspapers and Twitter across three pandemic phases (pre-pandemic, pandemic-core, post-pandemic), revealing a convergence in topic coverage between traditional and social media during COVID-19.
Figure 4: Distribution of individual thematic labels in newspapers and Twitter across pandemic phases. In contrast to the overarching domain level, individual labels exhibit pronounced differences between the two media, with Twitter showing more volatile and extreme shifts in topic salience.
CategoriesCorrelation
105 - Military: Negative0.93
504 - Welfare State Expansion0.89
303 - Governmental and Administrative Efficiency0.85
505 - Welfare State Limitation0.85
103 - Anti-Imperialism0.85
106 - Peace0.83
Table 2: Top and bottom thematic correlations of monthly ratios (DE vs. CH)
Figure 5: Monthly reporting ratios in German (DE) and Swiss (CH) news papers for the topics Federalism ( ρ=0.34\rho=0.34 ) and Education Expansion ( ρ=0.09\rho=0.09 ) show the lowest correlations in the dataset. This could reflect national differences such as more direct participatory democracy in Switzerland and differences in COVID-19 measures in schools.
Figure 6: Comparative analysis of Welfare State Expansion, Military, and Democracy reporting in Germany and Switzerland (2020–2022). Both countries show closely aligned trends in Military: Negative and Welfare State Expansion , reflecting shared responses to global events. In contrast, Democracy reveal pronounced national differences.
Figure 7: Monthly share of left-wing and right-wing topics in the public german discourse, classified based on the Manifesto Project coding scheme. Across both countries, left-wing and right-wing shares remain relatively stable and balanced throughout the observation period. A notable exception occurs in early 2022, where a pronounced spike in left-wing topics is observable in both countries, coinciding with the Russian invasion of Ukraine.

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