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ZENODO
Preprint . 2025
License: CC BY
Data sources: Datacite
ZENODO
Preprint . 2025
License: CC BY
Data sources: Datacite
ZENODO
Preprint . 2025
License: CC BY
Data sources: Datacite
https://dx.doi.org/10.48550/ar...
Article . 2025
License: CC BY
Data sources: Datacite
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Political Biases on X before the 2025 German Federal Election

Authors: Tabia, Tanzin Prama; Bagchi, Chhandak; Kalakonnavar, Vishal; Krauß, Paul; Grabowicz, Przemyslaw;

Political Biases on X before the 2025 German Federal Election

Abstract

This study examines whether German X users would see politically balanced news feeds if they followed comparable leading politicians from each federal parliamentary party of Germany. We address this question using an algorithmic audit tool and all publicly available posts published by 436 German politicians on X. We find that the default feed of X showed more content from far-right AfD than from other political parties. We analyze potential factors influencing feed content and the resulting political non-representativeness of X. Our findings suggest that engagement measures and unknown factors related to party affiliation contribute to the overrepresentation of extremes of the German political party spectrum in the default algorithmic feed of X.

Keywords

Social and Information Networks (cs.SI), FOS: Computer and information sciences, Computer Science - Computers and Society, Bias, Computers and Society (cs.CY), Computer Science - Social and Information Networks, Political sciences, Elections, Social Media

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green