No Echo in the Chambers of Political Interactions on Reddit
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Abstract (arXiv)
Echo chambers in online social networks, whereby users' beliefs are reinforced by interactions with like-minded peers and insulation from others' points of view, have been decried as a cause of political polarization. Here, we investigate their role in the debate around the 2016 US elections on Reddit, a fundamental platform for the success of Donald Trump. We identify Trump vs Clinton supporters and reconstruct their political interaction network. We observe a preference for cross-cutting political interactions between the two communities rather than within-group interactions, thus contradicting the echo chamber narrative. Furthermore, these interactions are asymmetrical: Clinton supporters are particularly eager to answer comments by Trump supporters. Beside asymmetric heterophily, users show assortative behavior for activity, and disassortative, asymmetric behavior for popularity. Our findings are tested against a null model of random interactions, by using two different approaches: a network rewiring which preserves the activity of nodes, and a logit regression which takes into account possible confounding factors. Finally, we explore possible socio-demographic implications. Users show a tendency for geographical homophily and a small positive correlation between cross-interactions and voter abstention. Our findings shed light on public opinion formation on social media, calling for a better understanding of the social dynamics at play in this context.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). First posted on arXiv 10 Feb 2021.
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Citing papers per year: 2022: 2; 2023: 2; 2024: 4; 2025: 1.
9 papers.
- 2024QuaLLM: An LLM-based Framework to Extract Quantitative Insights from Online Forumscited by 8
- 2022Cascade-based Echo Chamber Detectioncited by 6
- 2023Author as Character and Narrator: Deconstructing Personal Narratives from the r/AmITheAsshole Reddit Communitycited by 6
- 2024Algorithmic Drift: A Simulation Framework to Study the Effects of Recommender Systems on User Preferencescited by 5
- 2025Behavioral Homophily in Social Media via Inverse Reinforcement Learning: A Reddit Case Studycited by 5
- 2022"Double vaccinated, 5G boosted!": Learning Attitudes towards COVID-19 Vaccination from Social Mediacited by 0
- 2023On the Complexity of the Bipartite Polarization Problem: from Neutral to Highly Polarized Discussionscited by 0
- 2024Political Leaning Inference through Plurinational Scenarioscited by 0
- 2024Quantifying Extreme Opinions on Reddit Amidst the 2023 Israeli-Palestinian Conflictcited by 0
- 2025Behavioral Homophily in Social Media via Inverse Reinforcement Learning: A Reddit Case Study5 Feb 2025
- 2024Quantifying Extreme Opinions on Reddit Amidst the 2023 Israeli-Palestinian Conflict14 Dec 2024
- 2024Algorithmic Drift: A Simulation Framework to Study the Effects of Recommender Systems on User Preferences24 Sep 2024
- 2024Political Leaning Inference through Plurinational Scenarios12 Jun 2024
- 2024QuaLLM: An LLM-based Framework to Extract Quantitative Insights from Online Forums8 May 2024
- 2023On the Complexity of the Bipartite Polarization Problem: from Neutral to Highly Polarized Discussions21 Jul 2023
- 2023Author as Character and Narrator: Deconstructing Personal Narratives from the r/AmITheAsshole Reddit Community19 Jan 2023
- 2022Cascade-based Echo Chamber Detection9 Aug 2022
- 2022"Double vaccinated, 5G boosted!": Learning Attitudes towards COVID-19 Vaccination from Social Media27 Jun 2022