Users Polarization on Facebook and Youtube
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Abstract (arXiv)
On social media algorithms for content promotion, accounting for users preferences, might limit the exposure to unsolicited contents. In this work, we study how the same contents (videos) are consumed on different platforms -- i.e. Facebook and YouTube -- over a sample of 12M of users. Our findings show that the same content lead to the formation of echo chambers, irrespective of the online social network and thus of the algorithm for content promotion. Finally, we show that the users' commenting patterns are accurate early predictors for the formation of echo-chambers.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 10 Apr 2016.
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Citing papers per year: 2021: 2; 2022: 2; 2023: 2; 2024: 1; 2025: 1; 2026: 2.
10 papers.
- 2021A Survey on Echo Chambers on Social Media: Description, Detection and Mitigationcited by 11
- 2025The Lock-in Hypothesis: Stagnation by Algorithmcited by 11
- 2021Studying Fake News Spreading, Polarisation Dynamics, and Manipulation by Bots: a Tale of Networks and Languagecited by 6
- 2024More than Memes: A Multimodal Topic Modeling Approach to Conspiracy Theories on Telegramcited by 6
- 2022The Risks of Machine Learning Systemscited by 5
- 2023Rebalancing Social Feed to Minimize Polarization and Disagreementcited by 2
- 2022Emergent Instabilities in Algorithmic Feedback Loopscited by 1
- 2023On the Complexity of the Bipartite Polarization Problem: from Neutral to Highly Polarized Discussionscited by 0
- 2026Measuring Narrative Polarization in Online Discoursecited by 0
- 2026Ideological Isolation in Online Social Networks: A Survey of Computational Definitions, Metrics, and Mitigation Strategiescited by 0
- 2026Ideological Isolation in Online Social Networks: A Survey of Computational Definitions, Metrics, and Mitigation Strategies12 Jan 2026
- 2026Measuring Narrative Polarization in Online Discourse12 Jan 2026
- 2025The Lock-in Hypothesis: Stagnation by Algorithm6 Jun 2025
- 2024More than Memes: A Multimodal Topic Modeling Approach to Conspiracy Theories on Telegram11 Oct 2024
- 2023Rebalancing Social Feed to Minimize Polarization and Disagreement28 Aug 2023
- 2023On the Complexity of the Bipartite Polarization Problem: from Neutral to Highly Polarized Discussions21 Jul 2023
- 2022The Risks of Machine Learning Systems21 Apr 2022
- 2022Emergent Instabilities in Algorithmic Feedback Loops18 Jan 2022
- 2021A Survey on Echo Chambers on Social Media: Description, Detection and Mitigation9 Dec 2021
- 2021Studying Fake News Spreading, Polarisation Dynamics, and Manipulation by Bots: a Tale of Networks and Language13 Sep 2021