The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index.
Filter Bubbles, Echo Chambers, and Online News Consumption
Open accessAbstract
Online publishing, social networks, and web search have dramatically lowered the costs of producing, distributing, and discovering news articles. Some scholars argue that such technological changes increase exposure to diverse perspectives, while others worry that they increase ideological segregation. We address the issue by examining web-browsing histories for 50,000 US-located users who regularly read online news. We find that social networks and search engines are associated with an increase in the mean ideological distance between individuals. However, somewhat counterintuitively, these same channels also are associated with an increase in an individual’s exposure to material from his or her less preferred side of the political spectrum. Finally, the vast majority of online news consumption is accounted for by individuals simply visiting the home pages of their favorite, typically mainstream, news outlets, tempering the consequences—both positive and negative—of recent technological changes. We thus uncover evidence for both sides of the debate, while also finding that the magnitude of the effects is relatively modest.
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In the citing paper
“There is significant research on the ways in which algorithms produce search results that mirror people’s worldviews, but the majority of that work has been carried out on social networks [83,84].”
From Evolving Health Information–Seeking Behavior in the Context of Google AI Overviews, ChatGPT, and Alexa: Interview Study Using the Think-Aloud Protocol (2025) · cites this paper as [84]
In the citing paper
“Web traffic data suggest that relatively few Americans have heavily skewed information diets15–18”
From Like-minded sources on Facebook are prevalent but not polarizing (2023) · cites this paper as [16]
In the citing paper
“Pese a que son numerosos los estudios basados en la polarización afectiva y los medios de comunicación (Stroud, 2010;Flaxman et al., 2016;Tsfati & Nir, 2017;Rojo-Martínez et al., 2023;Torcal, 2023), no son tan frecuentes aquellos que estudian el nivel de uso de diferentes medios de forma integrada, asumiendo la condición híbrida del sistema mediático, y analizan según esta el grado de polarización”
From Política, uso de medios y polarización afectiva en España (2024) · cites this paper as Flaxman et al., 2016
In the citing paper
“Esta práctica cotidiana y hábito informativo convertiría a las sociedades occidentales menos tolerantes con aquellos puntos de vista opuestos a los propios (Jamieson y Capella, 2008) y con posiciones u opiniones más extremas, que devienen en una creciente polarización de la sociedad (Flaxman et al., 2016).”
From Homofilia, polarización afectiva y desinformación en Twitter. Caso de estudio sobre la crisis migratoria #Openarms (2021) · cites this paper as Flaxman et al., 2016
In the citing paper
“This is consistent with recent observational studies of online web browsing behavior which find that, with respect to political news, partisans di↵er in their typical media diet even as they do not completely retreat into echo chambers (see e.g., Peterson et al., ND, Flaxman et al., 2016, Guess, 2019).”
From Partisan Gaps in Political Information and Information-Seeking Behavior: Motivated Reasoning or Cheerleading? (2019) · cites this paper as Flaxman et al., 2016
In the citing paper
“This also reaffirms the fact that the negative effects of echo chambers in social networks, which are known to arise due to high levels of homophily in communication, might be overstated”
From Credibility of climate change denial in social media (2019) · cites this paper as Flaxman et al., 2016
In the citing paper
“Del Vicario et al. [48] and Flaxman et al. [134] demonstrated that contentconsidering methods effectively detect echo chambers formed through selective content exposure.”
From A systematic review of echo chamber research: comparative analysis of conceptualizations, operationalizations, and varying outcomes (2025) · cites this paper as [134]
In the citing paper
“Some studies observe reinforcement of this sort (92); others provide conflicting evidence in both magnitude and direction (93-96).”
From Misinformation in and about science (2021) · cites this paper as [94]
In the citing paper
“With the advent of the Internet, online media has become a widespread source of information and, subsequently, opinion formation5–9.”
From Negativity drives online news consumption (2023) · cites this paper as [5]
Citations
Cites
Birds of a Feather: Homophily in Social Networks
McPherson, M., Smith-Lovin, L., & Cook, J. M. (2001) · Annual Review of Sociology · doi:10.1146/annurev.soc.27.1.415 · Cited by 18,567
An Economic Theory of Democracy.
Banfield, E. C., & Downs, A. J. (1958) · Midwest Journal of Political Science · doi:10.2307/2109186 · Cited by 18,558
Data Analysis Using Regression and Multilevel/Hierarchical Models
Gelman, A., & Hill, J. (2006) · doi:10.1017/cbo9780511790942 · Cited by 13,597
Foundations of statistical natural language processing
Manning, C. D., & Schütze, H. (1999) · Cited by 9,816
On the limited memory BFGS method for large scale optimization
Liu, D. C., & Nocedal, J. M. (1989) · Mathematical Programming · doi:10.1007/bf01589116 · Cited by 9,062
(2011) · Cited by 4,430
Benkler, Y. R. (2017) · Yale University Press eBooks · doi:10.12987/9780300127232 · Cited by 3,728
Exposure to ideologically diverse news and opinion on Facebook
Bakshy, E., Messing, S., & Adamic, L. A. (2015) · Science · doi:10.1126/science.aaa1160 · Cited by 3,245
Broder, A. (2002) · ACM SIGIR Forum · doi:10.1145/792550.792552 · Cited by 1,944
Red Media, Blue Media: Evidence of Ideological Selectivity in Media Use
Iyengar, S., & Hahn, K. S. (2009) · Journal of Communication · doi:10.1111/j.1460-2466.2008.01402.x · Cited by 1,940
FILTER BUBBLE: Wie wir im Internet entmündigt werden
Pariser, E. (2012) · doi:10.3139/9783446431164 · Cited by 1,849
Google news personalization: scalable online collaborative filtering
Das, A., Datar, M., Garg, A., & Rajaram, S. (2007) · The Web Conference · doi:10.1145/1242572.1242610 · Cited by 1,833
The Development and Psychometric Properties of LIWC2015
Pennebaker, J. W., Boyd, R. L., Jordan, K., & Blackburn, K. (2015) · University of Texas at Austin · doi:10.15781/t25p41 · Cited by 1,674
The Fox News Effect: Media Bias and Voting
DellaVigna, S., & Kaplan, E. (2007) · The Quarterly Journal of Economics · doi:10.1162/qjec.122.3.1187 · Cited by 1,602
What Drives Media Slant? Evidence From U.S. Daily Newspapers
Gentzkow, M. A., & Shapiro, J. M. (2010) · Econometrica · doi:10.3982/ecta7195 · Cited by 1,559
The role of social networks in information diffusion
Bakshy, E., Rosenn, I., Marlow, C., & Adamic, L. (2012) · Proceedings of the 21st international conference on World Wide Web · doi:10.1145/2187836.2187907 · Cited by 1,526
What Drives Media Slant? Evidence from U.S. Daily NewspapersPreprint
Gentzkow, M., & Shapiro, J. M. (2006) · SSRN Electronic Journal · doi:10.2139/ssrn.947640 · Cited by 1,418
Social Pressure and Voter Turnout: Evidence from a Large-Scale Field Experiment
Gerber, A. S., GREEN, D. P., & Larimer, C. W. (2008) · American Political Science Review · doi:10.1017/s000305540808009x · Cited by 1,387
Gentzkow, M., & Shapiro, J. M. (2006) · Journal of Political Economy · doi:10.1086/499414 · Cited by 1,274
Mullainathan, S., & Shleifer, A. (2005) · American Economic Review · doi:10.1257/0002828054825619 · Cited by 1,236
Media and Political Polarization
Prior, M. (2013) · Annual Review of Political Science · doi:10.1146/annurev-polisci-100711-135242 · Cited by 1,125
Improving web search ranking by incorporating user behavior information
Agichtein, E., Brill, E., & Dumais, S. (2006) · International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · doi:10.1145/1148170.1148177 · Cited by 1,060
Groseclose, T., & Milyo, J. D. (2005) · The Quarterly Journal of Economics · doi:10.1162/003355305775097542 · Cited by 1,042
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
The group as a polarizer of attitudes.
Moscovici, S., & Zavalloni, M. (1969) · Journal of Personality and Social Psychology · doi:10.1037/h0027568 · Cited by 1,038
Ideological Segregation Online and Offline *
Gentzkow, M., & Shapiro, J. M. (2011) · The Quarterly Journal of Economics · doi:10.1093/qje/qjr044 · Cited by 980
Messing, S., & Westwood, S. J. (2014) · Communication Research · doi:10.1177/0093650212466406 · Cited by 902
Partisans without Constraint: Political Polarization and Trends in American Public Opinion
Baldassarri, D., & Gelman, A. (2008) · American Journal of Sociology · doi:10.1086/590649 · Cited by 874
Electoral Competition with Informed and Uninformed Voters
Baron, D. P. (1994) · American Political Science Review · doi:10.2307/2944880 · Cited by 638
Gentzkow, M. A., & Shapiro, J. M. (2005) · National Bureau of Economic Research · doi:10.3386/w11664 · Cited by 631
Sunstein, C. R. (2007) · Medical Entomology and Zoology · Cited by 621
What Drives Media Slant? Evidence from U.S. Daily Newspapers
Gentzkow, M. A., & Shapiro, J. M. (2006) · National Bureau of Economic Research · doi:10.3386/w12707 · Cited by 579
New Media and the Polarization of American Political Discourse
Baum, M., & Groeling, T. J. (2008) · Political Communication · doi:10.1080/10584600802426965 · Cited by 549
Biased assimilation, homophily, and the dynamics of polarization
Dandekar, P., Goel, A., & Lee, D. T. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1217220110 · Cited by 435
Measuring personalization of web search
Hannak, A., Sapiezynski, P., Molavi Kakhki, A., Krishnamurthy, B., Lazer, D., Mislove, A., & Wilson, C. (2013) · Proceedings of the 22nd international conference on World Wide Web · doi:10.1145/2488388.2488435 · Cited by 396
The structure of online diffusion networks
Goel, S., Watts, D. J., & Goldstein, D. G. (2012) · ACM Conference on Electronic Commerce (EC) · doi:10.1145/2229012.2229058 · Cited by 390
Self-citationTeevan, J. B., Ramage, D., & Morris, M. R. (2011) · ACM International Conference on Web Search and Data Mining (WSDM) · doi:10.1145/1935826.1935842 · Cited by 372
De‐individuation and group polarization in computer‐mediated communication
Spears, R., Lea, M., & Lee, S. (1990) · British Journal of Social Psychology · doi:10.1111/j.2044-8309.1990.tb00893.x · Cited by 359
Lawrence, E., Sides, J., & Farrell, H. (2010) · Perspectives on Politics · doi:10.1017/s1537592709992714 · Cited by 352
The Effect of Information on Voter Turnout: Evidence from a Natural Experiment
Lassen, D. D. (2004) · American Journal of Political Science · doi:10.1111/j.0092-5853.2005.00113.x · Cited by 335
Hosanagar, K., Fleder, D. M., Lee, D., & Buja, A. (2013) · Management Science · doi:10.1287/mnsc.2013.1808 · Cited by 264
The Seeds of Audience Fragmentation: Specialization in the Use of Online News Sites
Tewksbury, D. H. (2005) · Journal of Broadcasting & Electronic Media · doi:10.1207/s15506878jobem4903_5 · Cited by 247
Discussion effects on racial attitudes
Myers, D. G., & Bishop, G. D. (1970) · Science · doi:10.1126/science.169.3947.778 · Cited by 238
Presenting diverse political opinions
Munson, S. A., & Resnick, P. (2010) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/1753326.1753543 · Cited by 236
Real and perceived attitude agreement in social networks.
Goel, S., Mason, W., & Watts, D. J. (2010) · Journal of Personality and Social Psychology · doi:10.1037/a0020697 · Cited by 219
Self-citationBiased Assimilation, Homophily, and the Dynamics of Polarization
Dandekar, P., Goel, A., & Lee, D. (2012) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-35311-6_47 · Cited by 201
Web page revisitation revisited
Obendorf, H., Weinreich, H., Herder, E., & Mayer, M. (2007) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/1240624.1240719 · Cited by 171
What Happened on Deliberation Day?Preprint
Schkade, D. A., Sunstein, C. R., & Hastie, R. (2006) · SSRN Electronic Journal · doi:10.2139/ssrn.911646 · Cited by 143
Who Does What on the Web: A Large-Scale Study of Browsing Behavior
Goel, S., Hofman, J. M., & Sirer, M. I. (2021) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v6i1.14266 · Cited by 141
Self-citationImproving category specific Web search by learning query modifications
Glover, E. J., Flake, G. W., Lawrence, S., Birmingham, W. P., Kruger, A., Giles, C. L., & Pennock, D. M. (2002) · IEEE/IPSJ International Symposium on Applications and the Internet (SAINT) · doi:10.1109/saint.2001.905165 · Cited by 113
Improving Web Search Ranking by Incorporating User Behavior
Agichtein, E., Brill, E., & Dumais, S. (2006) · Cited by 76
The Impact of News Aggregators on Internet News Consumption: The Case of Localization
Athey, S. C., & Möbius, M. (2012) · Toulouse 1 Capitole Publications (Université Toulouse I Capitole) · Cited by 58
What Happened on Deliberation Day
Schkade, D. A. (2007) · California Law Review · doi:10.15779/z38740z · Cited by 52
Political Insights: Exploring partisanship in Web search queries
Borra, E., & Weber, I. G. (2012) · First Monday · doi:10.5210/fm.v17i7.4070 · Cited by 28
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Bakshy, E., Messing, S., & Adamic, L. A. (2015) · Science · doi:10.1126/science.aaa1160 · Cited by 3,245
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Metadata
- Authors
- Flaxman, S., Goel, S., & Rao, J. M.
- Affiliations
- University of Oxford (GB)
- Venue
- Public Opinion Quarterly
- Publisher
- Oxford University Press (OUP)
- Published
- 2016
- Volume
- 80
- Issue
- S1
- Pages
- 298-320
- ISSN
- 0033-362X (ISSN-L)
- 1537-5331
- OpenAlex
- W2303924600
- Cited by
- 1,992
- References
- 54
- Citations by year
- 2026: 166 · 2025: 177 · 2024: 174 · 2023: 213 · 2022: 277 · 2021: 256 · 2020: 251 · 2019: 228 · 2018: 146 · 2017: 66 · 2016: 18
- FWCI
- 436.55
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- Public Opinion Quarterly (publishedVersion)
- SSRN Electronic Journal (acceptedVersion)
- HighWire Press Open Archive (submittedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Media Influence and Politics
- Social Sciences › Communication › Social Media and Politics
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Keywords
- filter bubbles, echo chambers, online news consumption, ideological segregation, ideological distance, social networks, search engines, web browsing history, political polarization, information exposure
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