Gaisbauer, F., Pournaki, A., & Ohme, J. (2025). A political cartography of news sharing: Capturing story, outlet and content level of news circulation on Twitter. arXiv [cs.SI].
Summary
This paper offers a methodological intervention into the study of online news circulation, arguing that dominant approaches to partisan news sharing suffer from three recurring limitations: an oversimplified, often unidimensional measurement of political leaning; an exclusive focus on the outlet level while ignoring how individual stories and content travel; and an overconcentration in particular national contexts. In response, the authors propose a “political cartography” framework that maps news sharing on Twitter simultaneously across story, outlet, and content levels, and that constructs a more nuanced measure of the political leanings of news sharers. The contribution is primarily conceptual and methodological rather than a report of substantive empirical findings.
Key Contributions
- Introduces a “political cartography” framework for mapping online news circulation.
- Advances the measurement of political leaning beyond simple left–right scales in news-sharing research.
- Integrates story, outlet, and content levels into a single unified analytical approach.
- Delivers a methodological critique of the dominant paradigm in partisan news circulation studies.
Methods
The approach rests on analysis of news-sharing trace data from Twitter, examined across three nested levels — story, outlet, and content. Central to the design is a more nuanced (presumably multidimensional) measure of sharers’ political leaning, intended to replace the unidimensional left–right scales common in prior work. Specific datasets, sample sizes, and analytical techniques are not detailed in the available abstract.
Findings
- Substantive empirical findings are not specified in the available abstract; the paper’s value in this version lies in its methodological and conceptual proposals.
Connections
This paper sits within the tradition of using social-platform trace data to characterize partisan asymmetries in news exposure and sharing, engaging critically with the outlet-centric ideology-scoring approach exemplified by Bakshy2015-rn. Its multi-level and cross-story focus resonates with coordinated and story-level circulation work such as Giglietto2019-882f1900, Giglietto2019-e9be81c1, and Giglietto2020-6278a4aa, and its concern with measuring political leaning in shared content connects to computational estimation efforts like Le-Mens2025-qz.