Political Polarization in Online News Consumption
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Abstract (arXiv)
Political polarization appears to be on the rise, as measured by voting behavior, general affect towards opposing partisans and their parties, and contents posted and consumed online. Research over the years has focused on the role of the Web as a driver of polarization. In order to further our understanding of the factors behind online polarization, in the present work we collect and analyze Web browsing histories of tens of thousands of users alongside careful measurements of the time spent browsing various news sources. We show that online news consumption follows a polarized pattern, where users' visits to news sources aligned with their own political leaning are substantially longer than their visits to other news sources. Next, we show that such preferences hold at the individual as well as the population level, as evidenced by the emergence of clear partisan communities of news domains from aggregated browsing patterns. Finally, we tackle the important question of the role of user choices in polarization. Are users simply following the links proffered by their Web environment, or do they exacerbate partisan polarization by intentionally pursuing like-minded news sources? To answer this question, we compare browsing patterns with the underlying hyperlink structure spanned by the considered news domains, finding strong evidence of polarization in partisan browsing habits beyond that which can be explained by the hyperlink structure of the Web.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Apr 2021.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 3; 2024: 1; 2025: 1; 2026: 3.
9 papers.
- 2024Exploring Factual Entailment with NLI: A News Media Studycited by 4
- 2023Same Words, Different Meanings: Semantic Polarization in Broadcast Media Language Forecasts Polarization on Social Media Discoursecited by 2
- 2021A Machine Learning Pipeline to Examine Political Bias with Congressional Speechescited by 1
- 2023Modeling Political Orientation of Social Media Posts: An Extended Analysiscited by 0
- 2023All Polarized but Still Different: a Multi-factorial Metric to Discriminate between Polarization Behaviors on Social Mediacited by 0
- 2025KAN KAN Buff Signed Graph Neural Networks?cited by 0
- 2026Balancing Domestic and Global Perspectives: Evaluating Dual-Calibration and LLM-Generated Nudges for Diverse News Recommendationcited by 0
- 2026Triangulating Temporal Dynamics in Multilingual Swiss Online Newscited by 0
- 2026From Web(logs) to Web(AI): Questions, Platforms, and Methods across Twenty Editions of ICWSMcited by 0
- 2026From Web(logs) to Web(AI): Questions, Platforms, and Methods across Twenty Editions of ICWSM20 Sep 2026
- 2026Triangulating Temporal Dynamics in Multilingual Swiss Online News23 Mar 2026
- 2026Balancing Domestic and Global Perspectives: Evaluating Dual-Calibration and LLM-Generated Nudges for Diverse News Recommendation6 Mar 2026
- 2025KAN KAN Buff Signed Graph Neural Networks?1 Jan 2025
- 2024Exploring Factual Entailment with NLI: A News Media Study24 Jun 2024
- 2023All Polarized but Still Different: a Multi-factorial Metric to Discriminate between Polarization Behaviors on Social Media7 Dec 2023
- 2023Modeling Political Orientation of Social Media Posts: An Extended Analysis21 Nov 2023
- 2023Same Words, Different Meanings: Semantic Polarization in Broadcast Media Language Forecasts Polarization on Social Media Discourse20 Jan 2023
- 2021A Machine Learning Pipeline to Examine Political Bias with Congressional Speeches18 Sep 2021