Evidence of Demographic rather than Ideological Segregation in News Discussion on Reddit
Open accessAbstract
We evaluate homophily and heterophily among ideological and demographic groups in a typical opinion formation context: online discussions of current news. We analyze user interactions across five years in the r/news community on Reddit, one of the most visited websites in the United States. Then, we estimate demographic and ideological attributes of these users. Thanks to a comparison with a carefully-crafted network null model, we establish which pairs of attributes foster interactions and which ones inhibit them.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
On Reddit, studies find minimal evidence of echo chambers due to platform features encouraging cross-cutting exposure.
“On Reddit, studies find minimal evidence of echo chambers due to platform features encouraging cross-cutting exposure [17,61,63].”
From A systematic review of echo chamber research: comparative analysis of conceptualizations, operationalizations, and varying outcomes (2025) · cites this paper as [61]
The Introduction reports that ideological echo chambers were absent in the studied Reddit news discussions, and the Discussion says the findings strengthen evidence for their absence in generalist Reddit communities. But the Discussion notes that niche subreddits may form echo chambers and presents platform structure as a hypothesis for the difference, not an established cause of cross-cutting exposure. (LLM, conf=0.88)
Experimental — accuracy not yet measuredReddit's customizable recommendation algorithms encourage exposure to diverse viewpoints, reducing echo chamber effects compared to Facebook.
“For example, Reddit's customizable recommendation algorithms encourage exposure to diverse viewpoints, reducing echo chamber effects compared to Facebook [17,61,63].”
From A systematic review of echo chamber research: comparative analysis of conceptualizations, operationalizations, and varying outcomes (2025) · cites this paper as [61]
The Discussion (section 6; page not available in our copy) reports no ideological selective exposure in the Reddit news discussions studied and contrasts generalist Reddit communities with reported echo chambers on Facebook. Background and Related Work (section 2; page not available) also reports higher segregation of news consumption on Facebook than Reddit. The paper does not attribute this difference to customizable recommendation algorithms; it discusses a hypothesis about the platforms’ different structures instead. (LLM, conf=0.87)
Experimental — accuracy not yet measuredCulture or demographics drive polarization and echo chambers.
“novel research [61,64,92] finds that culture or demographics drive polarization and echo chambers.”
From A systematic review of echo chamber research: comparative analysis of conceptualizations, operationalizations, and varying outcomes (2025) · cites this paper as [61]
The Introduction describes demographic factors as a possible explanation for affective polarization, and the Discussion says the findings support a link between a divided society and polarization. But the Discussion also reports a lack of ideological echo chambers in generalist Reddit news discussions; the paper does not find that culture or demographics drive echo chambers. (LLM, conf=0.87)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
The Origins and Consequences of Affective Polarization in the United States
Iyengar, S., Lelkes, Y., Levendusky, M., Malhotra, N., & Westwood, S. J. (2019) · Annual Review of Political Science · doi:10.1146/annurev-polisci-051117-073034 · Cited by 3,317 · see citing works
Fear and loathing across party lines: New evidence on group polarization
Iyengar, S., & Westwood, S. J. (2015) · American Journal of Political Science · doi:10.1111/ajps.12152 · Cited by 2,452 · see citing works
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 4× · see citing works
“bers might not be an intrinsic characteristic of social media [15], but that the separation of demographic groups is observable during opinion formation online: fundamental societal divisions might be reflected also in social media.”
BackgroundInfluentialSelf-citationFilter Bubbles, Echo Chambers, and Online News Consumption
Flaxman, S., Goel, S., & Rao, J. M. (2016) · Public Opinion Quarterly · doi:10.1093/poq/nfw006 · Cited by 1,992 · see citing works
FILTER BUBBLE: Wie wir im Internet entmündigt werden
Pariser, E. (2012) · doi:10.3139/9783446431164 · Cited by 1,849 · see citing works
Echo chambers online?: Politically motivated selective exposure among Internet news users
Garrett, R. K. (2009) · Journal of Computer-Mediated Communication · doi:10.1111/j.1083-6101.2009.01440.x · Cited by 1,040 · see citing works
Are people incidentally exposed to news on social media? A comparative analysis
Fletcher, R., & Nielsen, R. K. (2018) · New Media & Society · doi:10.1177/1461444817724170 · Cited by 738 · see citing works
Political Polarization on Twitter
Conover, M., Ratkiewicz, J., Francisco, M., Goncalves, B., Menczer, F., & Flammini, A. (2021) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v5i1.14126 · Cited by 626 · cited 8× · see citing works
“Finally, Cinelli et al. [15] compared the presence of echo chambers around several controversial topics across four social media platforms (Twitter, Facebook, Reddit, and Gab), highlighting that Facebook shows higher segregation of news consumption than Reddit.”
BackgroundInfluentialQuattrociocchi, W., Scala, A., & Sunstein, C. R. (2016) · SSRN Electronic Journal · doi:10.2139/ssrn.2795110 · Cited by 389 · see citing works
Quantifying Controversy in Social Media
Garimella, K., De Francisci Morales, G., Gionis, A., & Mathioudakis, M. (2016) · Proceedings of the Ninth ACM International Conference on Web Search and Data Mining · doi:10.1145/2835776.2835792 · Cited by 147 · cited 1× · see citing works
“Since then, their result has been replicated several times, on different topics, and in various contexts [17, 19, 26, 28, 56].”
BackgroundTicking all the boxes? A comparative study of social sorting and affective polarization
Harteveld, E. (2021) · Electoral Studies · doi:10.1016/j.electstud.2021.102337 · Cited by 120 · see citing works
No echo in the chambers of political interactions on Reddit
De Francisci Morales, G., Monti, C., & Starnini, M. (2021) · Scientific Reports · doi:10.1038/s41598-021-81531-x · Cited by 98 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 46
- Samuel J Abrams and Morris P Fiorina. 2012. "The big sort" that wasn't: A skeptical reexamination. PS: Political Science & Politics 45, 2 (2012), 203-210. (Cited on 2)
- Max Aliapoulios, Emmi Bevensee, Jeremy Blackburn, Barry Bradlyn, Emiliano De Cristofaro, Gianluca Stringhini, and Savvas Zannettou. 2021. An early look at the parler online social network. arXiv preprint arXiv:2101.03820 (2021). (Cited on 7) · arXiv
- Jisun An, Daniele Quercia, and Jon Crowcroft. 2014. Partisan Sharing: Facebook Evidence and Societal Consequences. In COSN'14: ACM Conference on Online Social Networks. 13-24. (Cited on 2, 8)
- Eytan Bakshy, Solomon Messing, and Lada A Adamic. 2015. Exposure to ideolog- ically diverse news and opinion on Facebook. Science 348, 6239 (2015), 1130-1132. (Cited on 2, 8)
- Jason Baumgartner, Savvas Zannettou, Brian Keegan, Megan Squire, and Jeremy Blackburn. 2020. The pushshift reddit dataset. arXiv preprint arXiv:2001.08435 (2020). (Cited on 3) · arXiv
- A. Bessi, F. Zollo, M. Del Vicario, M. Puliga, A. Scala, G. Caldarelli, B. Uzzi, and W. Quattrociocchi. 2016. Users polarization on Facebook and Youtube. PLOS ONE 11, 8 (2016), e0159641. (Cited on 2)
- Paolo Boldi, Irene Crimaldi, and Corrado Monti. 2016. A network model charac- terized by a latent attribute structure with competition. Information Sciences 354 (2016), 236-256. (Cited on 3)
- Paolo Boldi and Corrado Monti. 2016. Llamafur: learning latent category matrix to fnd unexpected relations in wikipedia. In Proceedings of the 8th acm conference on web science. 218-222. (Cited on 3)
- Levi Boxell, Matthew Gentzkow, and Jesse M Shapiro. 2017. Greater Internet use is not associated with faster growth in political polarization among US demographic groups. Proceedings of the National Academy of Sciences 114, 40 (2017), 10612-10617. (Cited on 1)
- Arthur Capozzi, Gianmarco De Francisci Morales, Yelena Mejova, Corrado Monti, André Panisson, and Daniela Paolotti. 2021. Clandestino or Rifugiato? Anti- immigration Facebook Ad Targeting in Italy. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. 1-15. (Cited on 8)
- Alessandro Cossard, Gianmarco De Francisci Morales, Kyriaki Kalimeri, Yelena Mejova, Daniela Paolotti, and Michele Starnini. 2020. Falling into the Echo Chamber: The Italian Vaccination Debate on Twitter. In ICWSM '20: Fourteenth International AAAI Conference on Web and Social Media. 130-140. (Cited on 2)
- Wesley Cota, Silvio C. Ferreira, Romualdo Pastor-Satorras, and Michele Starnini. 2019. Quantifying echo chamber efects in information spreading over political communication networks. EPJ Data Science 8, 1 (2019), 35. https://doi.org/10. 1140/epjds/s13688-019-0213-9 (Cited on 1, 2) · DOI · Paper page
- Kareem Darwish. 2019. Quantifying polarization on twitter: the kavanaugh nomination. In International conference on social informatics. Springer, 188-201. (Cited on 2)
- Elizabeth Dubois and Grant Blank. 2018. The echo chamber is overstated: the moderating efect of political interest and diverse media. Information, communi- cation & society 21, 5 (2018), 729-745. (Cited on 1, 2)
- Erick Elejalde, Leo Ferres, and Rossano Schifanella. 2019. Understanding news outlets' audience-targeting patterns. EPJ Data Science 8, 1 (2019), 1-20. (Cited on 8)
- Linton C Freeman. 1978. Segregation in social networks. Sociological Methods & Research 6, 4 (1978), 411-429. (Cited on 2)
- Kiran Garimella, Gianmarco De Francisci Morales, Aristides Gionis, and Michael Mathioudakis. 2018. Political Discourse on Social Media: Echo Chambers, Gate- keepers, and the Price of Bipartisanship. In Proceedings of the 2018 World Wide Web Conference. 913-922. (Cited on 1, 2, 8)
- Venkata Rama Kiran Garimella and Ingmar Weber. 2017. A long-term analysis of polarization on Twitter. In Eleventh international AAAI conference on web and social media. (Cited on 2)
- James T Hamilton. 2011. All the news that's ft to sell. In All the News That's Fit to Sell. Princeton University Press. (Cited on 8)
- Tal Orian Harel, Jessica Katz Jameson, and Ifat Maoz. 2020. The normalization of hatred: Identity, afective polarization, and dehumanization on Facebook in the context of intractable political confict. Social Media+ Society 6, 2 (2020), 2056305120913983. (Cited on 1, 2)
- Bas Hofstra, Rense Corten, Frank Van Tubergen, and Nicole B Ellison. 2017. Sources of segregation in social networks: A novel approach using Facebook. American Sociological Review 82, 3 (2017), 625-656. (Cited on 2)
- Shanto Iyengar, Gaurav Sood, and Yphtach Lelkes. 2012. Afect, not ideology: a social identity perspective on polarization. Public opinion quarterly 76, 3 (2012), 405-431. (Cited on 1, 2)
- Gary C Jacobson. 2016. Polarization, gridlock, and presidential campaign politics in 2016. The ANNALS of the American Academy of Political and Social Science 667, 1 (2016), 226-246. (Cited on 2)
- Joohan Kim, Robert O Wyatt, and Elihu Katz. 1999. News, talk, opinion, partic- ipation: The part played by conversation in deliberative democracy. Political communication 16, 4 (1999), 361-385. (Cited on 2)
- Paul F Lazarsfeld, Robert K Merton, et al. 1954. Friendship as a social process: A substantive and methodological analysis. Freedom and control in modern society 18, 1 (1954), 18-66. (Cited on 1, 3)
- Angela M Lee and Hsiang Iris Chyi. 2014. When Newsworthy is Not Noteworthy: Examining the value of news from the audience's perspective. Journalism studies 15, 6 (2014), 807-820. (Cited on 8)
- Matthew Levendusky. 2009. The partisan sort: How liberals became Democrats and conservatives became Republicans. University of Chicago Press. (Cited on 2)
- Trevon D Logan and John M Parman. 2017. The national rise in residential segregation. The Journal of Economic History 77, 1 (2017), 127-170. (Cited on 2)
- Lilliana Mason and Julie Wronski. 2018. One tribe to bind them all: How our social group attachments strengthen partisanship. Political Psychology 39 (2018), 257-277. (Cited on 1, 3)
- Marshall McLuhan. 1994. Understanding media: The extensions of man. MIT press. (Cited on 7)
- Miller McPherson, Lynn Smith-Lovin, and James M Cook. 2001. Birds of a feather: Homophily in social networks. Annual review of sociology (2001), 415-444. (Cited on 1, 3)
- Martijn Meeter, Dirkjan JC Ochtman, Steve MJ Janssen, and Jaap MJ Murre. 2010. Of sports and politics: Predicting category-specifc retention of news events from demographic variables. European Journal of Cognitive Psychology 22, 1 (2010), 117-129. (Cited on 8)
- George Michael. 2017. The rise of the alt-right and the politics of polarization in America. Skeptic (Altadena, CA) 22, 2 (2017), 9-18. (Cited on 1)
- Kurt Miller, Michael Jordan, and Thomas Grifths. 2009. Nonparametric latent feature models for link prediction. Advances in neural information processing systems 22 (2009). (Cited on 3, 5)
- Rishabh Misra. 2022. News category dataset. arXiv preprint arXiv:2209.11429 (2022). (Cited on 4) · arXiv
- Michael Molloy and Bruce Reed. 1995. A critical point for random graphs with a given degree sequence. Random structures & algorithms 6, 2-3 (1995), 161-180. (Cited on 5)
- Corrado Monti and Paolo Boldi. 2017. Estimating latent feature-feature interac- tions in large feature-rich graphs. Internet Mathematics 1, 1 (2017), 2640. (Cited on 3, 5)
- Alfredo Jose Morales, Javier Borondo, Juan Carlos Losada, and Rosa M Benito. 2015. Measuring political polarization: Twitter shows the two sides of Venezuela. Chaos: An Interdisciplinary Journal of Nonlinear Science 25, 3 (2015), 033114. (Cited on 2)
- Krzysztof Nowicki and Tom A B Snijders. 2001. Estimation and prediction for stochastic blockstructures. Journal of the American statistical association 96, 455 (2001), 1077-1087. (Cited on 3)
- Judea Pearl. 2009. Causality. Cambridge University Press. (Cited on 5)
- Jefrey Pennington, Richard Socher, and Christopher D Manning. 2014. Glove: Global vectors for word representation. In Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP). 1532-1543. (Cited on 4)
- Cesare Rollo, Gianmarco De Francisci Morales, Corrado Monti, and André Panis- son. 2022. Communities, Gateways, and Bridges: Measuring Attention Flow in the Reddit Political Sphere. In Social Informatics: 13th International Conference, SocInfo 2022, Glasgow, UK, October 19-21, 2022, Proceedings. Springer, 3-19. (Cited on 7)
- Thomas C Schelling. 1969. Models of segregation. The American economic review 59, 2 (1969), 488-493. (Cited on 2)
- Ana Lucía Schmidt, Fabiana Zollo, Antonio Scala, Cornelia Betsch, and Walter Quattrociocchi. 2018. Polarization of the vaccination debate on Facebook. Vaccine 36, 25 (2018), 3606-3612. (Cited on 2)
- Cass R Sunstein. 2005. Why societies need dissent. Vol. 9. Harvard University Press. (Cited on 2)
- Isaac Waller and Ashton Anderson. 2021. Quantifying social organization and political polarization in online platforms. Nature 600, 7888 (2021), 264-268. (Cited on 2, 3)
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
- Authors
- Monti, C., D'Ignazi, J., Starnini, M., & De Francisci Morales, G.
- Affiliations
- CENTAI, Italy
- Institute for Scientific Interchange (IT)
- Venue
- Proceedings of the ACM Web Conference 2023
- Publisher
- ACM
- Published
- 2023-04-30
- Pages
- 2777-2786
- OpenAlex
- W4321174293
- Cited by
- 26
- References
- 12
- Citations by year
- 2026: 9 · 2025: 7 · 2024: 6 · 2023: 4
- FWCI
- 30.98
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- International World Wide Web Conference (WWW) (publishedVersion)
- arXiv (Cornell University) (submittedVersion, cc-by)
- Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano) (submittedVersion, other-oa)
- arXiv (Cornell University) (cc-by)
- Topics
- Social Sciences › Communication › Social Media and Politics
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Opinion Dynamics and Social Influence
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Keywords
- homophily, heterophily, ideological segregation, user interaction networks, opinion formation, ideological polarization
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 ›
Are you an author, or do you see a problem with this page? Request a review