Introducing a Political Cartography of News Sharing

Capturing Story, Outlet and Content Level of News Circulation on Twitter

Authors

  • Felix Gaisbauer Weizenbaum Institute, Berlin, DE https://orcid.org/0000-0003-2465-5637
  • Armin Pournaki Max Planck Institute for Mathematics in the Sciences, Leipzig, DE; Laboratoire Lattice, CNRS & ENS-PSL & Université Sorbonne nouvelle, Paris, FR; Sciences Po, médialab, Paris, FR
  • Jakob Ohme Weizenbaum Institute, Berlin, DE

DOI:

https://doi.org/10.5117/CCR2026.1.5.GAIS

Keywords:

news sharing, network embeddings, topic models, digital trace data, social media, Twitter

Abstract

News sharing on digital platforms shapes the digital spaces millions of users navigate. Trace data from these platforms also enables researchers to study online news circulation. In this context, research on the types of news shared by users of differential political leaning has received considerable attention. We argue that most existing approaches (i) rely on an overly simplified measurement of political leaning, (ii) consider only the outlet level in their analyses, and/or (iii) study news circulation among partisans by making ex-ante distinctions between partisan and non-partisan news. In this methodological contribution, we introduce a research pipeline that allows a systematic mapping of news sharing both with respect to source and content. As a proof of concept, we demonstrate insights that otherwise remain unnoticed: Diversification of news sharing along the second political dimension; topic-dependent sharing of outlets; some outlets catering different items to different audiences.

Published

2026-06-01

Issue

Section

Research Article (regular issue)

How to Cite

Gaisbauer, F., Pournaki, A., & Ohme, J. (2026). Introducing a Political Cartography of News Sharing: Capturing Story, Outlet and Content Level of News Circulation on Twitter. Computational Communication Research, 8(1). https://doi.org/10.5117/CCR2026.1.5.GAIS