Network polarization, filter bubbles, and echo chambers: an annotated review of measures and reduction methods
Open accessAbstract
Polarization arises when the underlying network connecting the members of a community or society becomes characterized by highly connected groups with weak intergroup connectivity. The increasing polarization, the strengthening of echo chambers, and the isolation caused by information filters in social networks are increasingly attracting the attention of researchers from different areas of knowledge such as computer science, economics, and social and political sciences. This work presents an annotated review of network polarization measures and models used to handle the polarization. Several approaches for measuring polarization in graphs and networks were identified, including those based on homophily, modularity, random walks, and balance theory. The strategies used for reducing polarization include methods that propose edge or node editions (including insertions or deletions as well as edge weight modifications), changes in social network design, or changes in the recommendation systems embedded in these networks.
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Group-level homophily aggregates the homophily of individual group members to assess group polarization.
“Group-Level Homophily: Aggregates the homophily of individual group members to assess group polarization [25].”
From A systematic review of echo chamber research: comparative analysis of conceptualizations, operationalizations, and varying outcomes (2025) · cites this paper as [25]
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The echo chamber effect on social media
Cinelli, M., De Francisci Morales, G., Galeazzi, A., Quattrociocchi, W., & Starnini, M. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2023301118 · Cited by 2,092 · cited 2× · see citing works
“[23], echo chambers are environments in which the opinions or beliefs of people about some topic are reinforced due to repeated interactions with peers or sources having similar tendencies and attitudes.”
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“They observed that, as the conflict intensifies, the RWC and the standard deviation of the overall sentiment expressed by the opposing groups are positively correlated and increase in unison.)”
BackgroundMethodInfluentialDebunking in a world of tribes
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“They observed that, as the conflict intensifies, the RWC and the standard deviation of the overall sentiment expressed by the opposing groups are positively correlated and increase in unison.)”
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Cited by
Sorted by citations
Hartmann, D., Wang, S. M., Pohlmann, L., & Berendt, B. (2025) · Journal of Computational Social Science · doi:10.1007/s42001-025-00381-z · Cited by 59 · see citing works
DSP: A Statistically-Principled Structural Polarization Measure
Preti, G., Riondato, M., Gionis, A., & De Francisci Morales, G. (2026) · Proceedings of the Nineteenth ACM International Conference on Web Search and Data Mining · doi:10.1145/3773966.3777942
- Authors
- Interian, R., G. Marzo, R., Mendoza, I., & Ribeiro, C. C.
- Affiliations
- Institute of Computing Universidade Federal Fluminense Niterói RJ 24210‐346 Brazil
- Universidade Federal Fluminense (BR)
- Venue
- International Transactions in Operational Research
- Publisher
- Wiley
- Published
- 2022-10-21
- Volume
- 30
- Issue
- 6
- Pages
- 3122-3158
- ISSN
- 0969-6016 (ISSN-L)
- 1475-3995
- OpenAlex
- W4307169212
- Cited by
- 67
- References
- 10
- Citations by year
- 2026: 20 · 2025: 27 · 2024: 14 · 2023: 6
- FWCI
- 4.43
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- International Transactions in Operational Research (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro (E‐26/204.200/2021, E‐26/200.330/2020, E‐26/200.926/2021)
- Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (001)
- Conselho Nacional de Desenvolvimento Científico e Tecnológico (143289/2021‐7, 309869/2020‐0)
- Topics
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Opinion Dynamics and Social Influence
- Social Sciences › Communication › Social Media and Politics
- Keywords
- filter bubbles, echo chambers, polarization measures, homophily, modularity, random walks, balance theory, social networks, social network design, recommender systems
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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