The DOI matches its Crossref record; 63 of the 64 references it cites were found in a registry or an index.
Red Media, Blue Media: Evidence of Ideological Selectivity in Media Use
Abstract
We show that the demand for news varies with the perceived affinity of the news organization to the consumer’s political preferences. In an experimental setting, conservatives and Republicans preferred to read news reports attributed to Fox News and to avoid news from CNN and NPR. Democrats and liberals exhibited exactly the opposite syndrome—dividing their attention equally between CNN and NPR, but avoiding Fox News. This pattern of selective exposure based on partisan affinity held not only for news coverage of controversial issues but also for relatively “soft” subjects such as crime and travel. The tendency to select news based on anticipated agreement was also strengthened among more politically engaged partisans. Overall, these results suggest that the further proliferation of new media and enhanced media choices may contribute to the further polarization of the news audience.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
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?
In the citing paper
“The directional (or defensive) motivation leads to selective exposure, encouraging individuals to seek information (or news sources) that they believe is congenial to their existing attitudes (Iyengar & Hahn, 2009;Stroud, 2011).”
From Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization (2020) · cites this paper as Iyengar & Hahn, 2009
In the citing paper
“As a result of this transformation, individuals are being increasingly exposed to only information that reinforces their existing views, thus avoiding challenging opinions (Sunstein 2001; Garrett 2009; Iyengar and Hahn 2009).”
From Birds of the Same Feather Tweet Together: Bayesian Ideal Point Estimation Using Twitter Data (2015) · cites this paper as Iyengar and Hahn 2009
In the citing paper
“This generates a so-called echo-chamber environment that fosters social extremism and political polarization.”
From Birds of the Same Feather Tweet Together: Bayesian Ideal Point Estimation Using Twitter Data (2015) · cites this paper as Iyengar and Hahn 2009
Citations
Cites
A Theory of Cognitive Dissonance
Festinger, L. (1957) · doi:10.1515/9781503620766 · Cited by 24,241 · cited 1×
“The argument that people prefer to approach supportive over nonsupportive information precedes the onset of new media and dates back to the heyday of cognitive consistency theories in the 1950s (Festinger, 1957).”
BackgroundAdvances In Experimental Social Psychology
(2022) · Advances in experimental social psychology · doi:10.1016/s0065-2601(22)x0002-6 · Cited by 22,559
A Theory of Cognitive Dissonance
Morvan, C., & O’Connor, A. (2017) · Macat Library eBooks · doi:10.4324/9781912282432 · Cited by 18,284
Limited-Dependent and Qualitative Variables in Econometrics
Maddala, G. S. (1983) · Cambridge University Press eBooks · doi:10.1017/cbo9780511810176 · Cited by 13,268
Hapeman, D. E., & Agresti, A. (1991) · Technometrics · doi:10.1080/00401706.1991.10484817 · Cited by 9,407
Regression Models for Categorical and Limited Dependent Variables.
MTW, & Long, J. S. (1997) · Journal of the American Statistical Association · doi:10.2307/2965458 · Cited by 6,891
An Introduction to Categorical Data Analysis
Agresti, A. (2006) · Wiley series in probability and statistics · doi:10.1002/0470114754 · Cited by 6,775
Regression Models for Categorical and Limited Dependent Variables
Calvin, J. A., & Long, J. S. (1998) · Technometrics · doi:10.2307/1271407 · Cited by 5,290
Estimating Discrete-Choice Models of Product Differentiation
Berry, S. (1994) · The RAND Journal of Economics · doi:10.2307/2555829 · Cited by 2,835
The measurement of urban travel demand
McFadden, D. L. (1974) · Journal of Public Economics · doi:10.1016/0047-2727(74)90003-6 · Cited by 2,576
Research works printed but not linked: 12
- Bumiller, 200823, McCain gathers support and donations in aftermath of article in The Times, The New York Times, p. A13
- Fiorina, 2005, Culture wars? The myth of polarized America
- Fox, 1997, Applied regression, linear models, and related methods
- Greene, 2003, Econometric analysis
- Hill, 2007, The opt-in internet panel: Survey mode, sampling methodology and the implications for political research
- Iyengar, 2007, Media and politics: A citizen’s guide
- Jacobson, 2000, Polarized politics, 9
- Pew Research Center for the People and Press, 2004, Online news audience larger, more diverse: News audience increasingly polarized
- Rutenberg, 200821, For McCain, self-confidence on ethics poses its own risk, The New York Times
- Sears, 1968, Theories of cognitive consistency: A sourcebook, 777
- Smith, 1997, What the people want from the press
- Steinberg, 20076, Cable channel nods to ratings and leans left, The New York Times
Cited by
Sorted by citations
Items 401–500 of 1,001
Hmielowski, J. D., Beam, M. A., & Hutchens, M. J. (2015) · International Journal of Public Opinion Research · doi:10.1093/ijpor/edv012 · Cited by 46
Epistemic Factors in Selective Exposure and Political Misperceptions on the Right and Left
Meirick, P. C., & Bessarabova, E. (2015) · Analyses of Social Issues and Public Policy · doi:10.1111/asap.12101 · Cited by 45
The complex link between filter bubbles and opinion polarization
Keijzer, M. A., & Mäs, M. (2022) · Data Science · doi:10.3233/ds-220054 · Cited by 49
Schäfer, S., Aaldering, L., & Lecheler, S. K. (2022) · Mass Communication & Society · doi:10.1080/15205436.2022.2125406 · Cited by 46
Catapano, R., Tormala, Z. L., & Rucker, D. D. (2019) · Psychological Science · doi:10.1177/0956797618822697 · Cited by 50
Insta-echoes: Selective exposure and selective avoidance on Instagram
Parmelee, J. H., & Roman, N. (2020) · Telematics and Informatics · doi:10.1016/j.tele.2020.101432 · Cited by 43
Żerebecki, B. G., Opree, S. J., Hofhuis, J., & Janssen, S. (2021) · Sociology Compass · doi:10.1111/soc4.12906 · Cited by 56
Billionaires in World Politics
Hägel, P. (2020) · doi:10.1093/oso/9780198852711.001.0001 · Cited by 44
Polarization as a Function of Citizen Predispositions and Exposure to News on the Internet
Tewksbury, D., & Riles, J. M. (2015) · Journal of Broadcasting & Electronic Media · doi:10.1080/08838151.2015.1054996 · Cited by 42
Brenes-Peralta, C., Wojcieszak, M., Yphtach Lelkes, B., & de Vreese, C. H. (2016) · Journalism & Mass Communication Quarterly · doi:10.1177/1077699016654681 · Cited by 47
INCOME INEQUALITY, MEDIA FRAGMENTATION, AND INCREASED POLITICAL POLARIZATION
Duca, J. V., & Saving, J. L. (2016) · Contemporary Economic Policy · doi:10.1111/coep.12191 · Cited by 42
Lee, F. L. F., Chan, M., Chen, H., Nielsen, R. K., & Fletcher, R. (2019) · Journalism Studies · doi:10.1080/1461670x.2019.1586567 · Cited by 45
Hameleers, M. (2019) · Mass Communication & Society · doi:10.1080/15205436.2019.1655768 · Cited by 44
van der Meer, T. G. L. A., & Hameleers, M. (2020) · New Media & Society · doi:10.1177/1461444820946455 · Cited by 47
The Public Service Approach to Recommender Systems: Filtering to Cultivate
Hildén, J. (2021) · Television & New Media · doi:10.1177/15274764211020106 · Cited by 58
Cognitive cascades: How to model (and potentially counter) the spread of fake news
Rabb, N., Cowen, L., de Ruiter, J. P., & Scheutz, M. J. (2022) · PLoS ONE · doi:10.1371/journal.pone.0261811 · Cited by 46
Digital Media and Perceptions of Source Credibility in Political Communication
Flanagin, A. J., & Metzger, M. J. (2014) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780199793471.013.65 · Cited by 44
Computer-Mediated False Consensus: Radical Online Groups, Social Networks and News Media
Wojcieszak, M. (2011) · Mass Communication & Society · doi:10.1080/15205436.2010.513795 · Cited by 43
Holman, M. R., & Lay, J. C. (2018) · Journal of Political Marketing · doi:10.1080/15377857.2018.1478656 · Cited by 42
Impact of Customizability Technology on Political Polarization
Dylko, I. B., Dolgov, I., Hoffman, W. B., Eckhart, N. R., Molina, M. D., & Aaziz, O. (2017) · Journal of Information Technology & Politics · doi:10.1080/19331681.2017.1354243 · Cited by 45
Believing and Sharing Information by Fake Sources: An Experiment
Bauer, P. C., & von Hohenberg, B. C. (2020) · Political Communication · doi:10.1080/10584609.2020.1840462 · Cited by 54
Alyukov, M. (2022) · Europe Asia Studies · doi:10.1080/09668136.2021.2016633 · Cited by 54
A structural hermeneutics of The O’Reilly Factor
Norton, M. (2011) · Theory and Society · doi:10.1007/s11186-011-9143-7 · Cited by 40
The Message Matters: The Influence of Fact-Checking on Evaluations of Political Messages
Wintersieck, A., Fridkin, K. L., & Kenney, P. J. (2018) · Journal of Political Marketing · doi:10.1080/15377857.2018.1457591 · Cited by 42
Bartels, B. L., & Johnston, C. D. (2020) · Cited by 41
Polarised social media discourse during COVID-19 pandemic: evidence from YouTube
Gupta, S., Jain, G., & Tiwari, A. A. (2022) · Behaviour and Information Technology · doi:10.1080/0144929x.2022.2059397 · Cited by 43
Marietta, M., & Barker, D. C. (2019) · doi:10.1093/oso/9780190677176.001.0001 · Cited by 102
Ridout, T. N., Fowler, E. F., Franz, M. M., & Goldstein, K. M. (2017) · American Politics Research · doi:10.1177/1532673x17721479 · Cited by 41
Bots and Computational Propaganda: Automation for Communication and Control
Woolley, S. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108890960.006 · Cited by 42
Choi, D.-H., & Shin, D. (2016) · Personality and Individual Differences · doi:10.1016/j.paid.2016.11.022 · Cited by 44
Polarization, Partisan Sorting, and the Politics of Education
Houston, D. M. (2024) · American Educational Research Journal · doi:10.3102/00028312241228280 · Cited by 43
Media Trust in a Community Context
Yamamoto, M., Lee, T., & Ran, W. (2014) · Communication Research · doi:10.1177/0093650214565894 · Cited by 43
Kim, Y., Chen, H., & Wang, Y. (2016) · Journal of Broadcasting & Electronic Media · doi:10.1080/08838151.2016.1203318 · Cited by 38
Social media and political partisanship – A subaltern public sphere’s role in democracy
Lee, P. S. N., So, C. Y. K., Lee, F. L. F., Leung, L. W., & Chan, M. (2018) · Telematics and Informatics · doi:10.1016/j.tele.2018.06.007 · Cited by 43
Fostering Civil Discourse Online
Rho, E. H. R., Mark, G. J., & Mazmanian, M. (2018) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3274416 · Cited by 41
Schumann, S., Boer, D., Hanke, K., & Liu, J. (2021) · Information, Communication & Society · doi:10.1080/1369118x.2019.1668455 · Cited by 38
Facts and Where to Find Them: Empirical Research on Internet Platforms and Content Moderation
Keller, D., & Leerssen, P. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108890960.011 · Cited by 39
Gollust, S. E., Vogel, R. I., Rothman, A. J., Yzer, M. C., Fowler, E. F., & Nagler, R. H. (2020) · Preventive Medicine · doi:10.1016/j.ypmed.2020.106278 · Cited by 38
The Influence of Unknown Media on Public Opinion: Evidence from Local and Foreign News Sources
Peterson, E., & Allamong, M. B. (2021) · American Political Science Review · doi:10.1017/s0003055421001234 · Cited by 45
Blandi, L., Sabbatucci, M., Dallagiacoma, G., Alberti, F., Bertuccio, P., & Odone, A. (2022) · Vaccines · doi:10.3390/vaccines10111822 · Cited by 55
Nechushtai, E., Zamith, R., & Lewis, S. C. (2023) · Mass Communication & Society · doi:10.1080/15205436.2023.2173609 · Cited by 49
Speaking Out of Both Sides of Their Mouths
Crawford, J. T., Kay, S. A., & Duke, K. E. (2015) · Social Psychological and Personality Science · doi:10.1177/1948550614566858 · Cited by 40
Arendt, F., Steindl, N., & Kümpel, A. S. (2016) · Journal of Communication · doi:10.1111/jcom.12256 · Cited by 43
Porumbescu, G. (2017) · International Public Management Journal · doi:10.1080/10967494.2016.1269859 · Cited by 37
Conflict-Framed News, Self-Categorization, and Partisan Polarization
Han, J., & Federico, C. M. (2017) · Mass Communication & Society · doi:10.1080/15205436.2017.1292530 · Cited by 42
NARİN, B. (2018) · SELÇUK ÜNİVERSİTESİ İLETİŞİM FAKÜLTESİ AKADEMİK DERGİSİ · doi:10.18094/josc.340471 · Cited by 46
Zheng, P., & Shahin, S. (2018) · Information Communication & Society · doi:10.1080/1369118x.2018.1503697 · Cited by 44
Income Inequality and Political Polarization: Time Series Evidence Over Nine Decades
Duca, J. V., & Saving, J. L. (2015) · Review of Income and Wealth · doi:10.1111/roiw.12162 · Cited by 37
Political Preferences, Knowledge, and Misinformation About COVID-19: The Case of Brazil
Gramacho, W. G., Turgeon, M., Kennedy, J., Stabile, M., & Mundim, P. S. (2021) · Frontiers in Political Science · doi:10.3389/fpos.2021.646430 · Cited by 41
Esau, K., Choucair, T. D. S., Vilkins, S., Svegaard, S. F. K., Bruns, A., O’Connor-Farfan, K. S., & Lubicz-Zaorski, C. (2024) · Information Communication & Society · doi:10.1080/1369118x.2024.2413127 · Cited by 52
To Unite and Divide: The Polarizing Effect of Presidential Debates
Warner, B. R., & McKinney, M. S. (2013) · Communication Studies · doi:10.1080/10510974.2013.832341 · Cited by 37
Lin, M., Haridakis, P. M., & Hanson, G. L. (2016) · Journal of Broadcasting & Electronic Media · doi:10.1080/08838151.2016.1203316 · Cited by 36
Simmons, A. D. (2017) · Social Forces · doi:10.1093/sf/sox031 · Cited by 36
Kim, Y. (2018) · International Journal of Public Opinion Research · doi:10.1093/ijpor/edy032 · Cited by 44
Rau, J. P., & Stier, S. (2019) · Zeitschrift für Vergleichende Politikwissenschaft · doi:10.1007/s12286-019-00429-1 · Cited by 44
Digital Disinformation and Preventive Actions: Perceptions of Users from Argentina, Chile, and Spain
Rodríguez-Virgili, J., Serrano-Puche, J., & Fernández, C. B. (2021) · Media and Communication · doi:10.17645/mac.v9i1.3521 · Cited by 42
Fear of COVID-19: What Causes Fear and How Individuals Cope with It
Li, R. (2021) · Health Communication · doi:10.1080/10410236.2021.1901423 · Cited by 36
Memory for Positive and Negative Political TV Ads: The Role of Partisanship and Gamma Power
Morey, A. C. (2017) · Political Communication · doi:10.1080/10584609.2016.1266534 · Cited by 35
Leave and Remain voters’ knowledge of the EU after the referendum of 2016
Carl, N., Richards, L., & Heath, A. (2018) · Electoral Studies · doi:10.1016/j.electstud.2018.11.003 · Cited by 38
Thibodeau, P. H., Peebles, M. M., Grodner, D. J., & Durgin, F. H. (2013) · Political Psychology · doi:10.1111/pops.12100 · Cited by 34
Cho, J., & Ha, Y. (2012) · Political Communication · doi:10.1080/10584609.2012.671233 · Cited by 35
Forging Bonds and Burning Bridges
Suhay, E., Blackwell, A., Roche, C., & Bruggeman, L. (2014) · American Politics Research · doi:10.1177/1532673x14553834 · Cited by 37
Parks, P. (2019) · Environmental Communication · doi:10.1080/17524032.2019.1611614 · Cited by 35
Echo chambers and social mediators in public advocacy issue networks
Tsai, W. S., Tao, W., Chuan, C., & Hong, C. (2020) · Public Relations Review · doi:10.1016/j.pubrev.2020.101882 · Cited by 36
Zhang, Y., Shah, D. V., Pevehouse, J. C. W., & Valenzuela, S. (2022) · The International Journal of Press/Politics · doi:10.1177/19401612211072793 · Cited by 42
Will the Personalization of Online Social Networks Foster Opinion Polarization?Preprint
Mäs, M., & Bischofberger, L. (2015) · SSRN Electronic Journal · doi:10.2139/ssrn.2553436 · Cited by 39
Fair and Balanced News or a Difference of Opinion? Why Opinion Shows Matter for Media Effects
Smith, G. R., & Searles, K. (2012) · Political Research Quarterly · doi:10.1177/1065912912465922 · Cited by 35
Outrageous political opinion and political anxiety in the US
Sobieraj, S., Berry, J. M., & Connors, A. (2013) · Poetics · doi:10.1016/j.poetic.2013.06.001 · Cited by 36
Donsbach, W., & Mothes, C. (2013) · Annals of the International Communication Association · doi:10.1080/23808985.2013.11679124 · Cited by 35
Design, Identification, and Sensitivity Analysis for Patient Preference Trials
Knox, D., Yamamoto, T., Baum, M., & Berinsky, A. J. (2019) · Journal of the American Statistical Association · doi:10.1080/01621459.2019.1585248 · Cited by 34
Schmuck, D., Tribastone, M., Matthes, J., Marquart, F., & Bergel, E. M. (2019) · Journal of Media Psychology Theories Methods and Applications · doi:10.1027/1864-1105/a000265 · Cited by 34
Exposure to opposing reasons reduces negative impressions of ideological opponents
Stanley, M. L., Whitehead, P. S., Sinnott-Armstrong, W. P., & Seli, P. (2020) · Journal of Experimental Social Psychology · doi:10.1016/j.jesp.2020.104030 · Cited by 35
Twitter made me do it! Twitter's tonal platform incentive and its effect on online campaigning
Mueller, S. D., & Sältzer, M. (2020) · Information Communication & Society · doi:10.1080/1369118x.2020.1850841 · Cited by 35
Wu, S., & Resnick, P. (2021) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v15i1.18105 · Cited by 34
Anti-Islamic sentiment and media framing during the 9/11 decade
Smith, C. E. (2013) · Cited by 34
New ICTs and the Study of Political Communication
Garrett, R., Bimber, B., de Zúñiga, H. G., Heinderyckx, F., Kelly, J., & Smith, M. A. (2012) · Dépôt institutionnel de l'Université libre de Bruxelles (Université Libre de Bruxelles) · Cited by 34
Explaining Misperceptions of CrimePreprint
Esberg, J., & Mummolo, J. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3208303 · Cited by 34
“Everything is Biased”: Populist Supporters’ Folk Theories of Journalism
Miro, C. J. (2023) · The International Journal of Press/Politics · doi:10.1177/19401612231197617 · Cited by 33
Does affective polarization contribute to democratic backsliding in America?
Druckman, J. N., Green, D. P., & Iyengar, S. (2023) · The ANNALS of the American Academy of Political and Social Science · doi:10.1177/00027162241228952 · Cited by 33
Self-citationPresidential Agenda-Setting of Traditional and Nontraditional News Media
Eshbaugh‐Soha, M. (2015) · Political Communication · doi:10.1080/10584609.2014.958261 · Cited by 33
Evolution of News Frames During the 2011 Egyptian Revolution
Guzman, A. L. (2015) · Journalism & Mass Communication Quarterly · doi:10.1177/1077699015606677 · Cited by 33
How Does Treatment Self-Selection Affect Inferences About Political Communication?
Leeper, T. J. (2017) · Journal of Experimental Political Science · doi:10.1017/xps.2017.1 · Cited by 33
Democratic Creative Destruction? The Effect of a Changing Media Landscape on Democracy
Nielsen, R. K., & Fletcher, R. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108890960.008 · Cited by 35
Shin, J. (2020) · Social Media + Society · doi:10.1177/2056305120981039 · Cited by 39
Box‐Steffensmeier, J. M., & Moses, L. M. (2021) · Science Advances · doi:10.1126/sciadv.abg2898 · Cited by 33
How Political Ideology Shapes Preferences for Observably Inferior Products
Lisjak, M., & Ordabayeva, N. (2022) · Journal of Consumer Research · doi:10.1093/jcr/ucac030 · Cited by 33
Choi, J. (2016) · Journal of Computer-Mediated Communication · doi:10.1111/jcc4.12176 · Cited by 33
Torcal, M., Santana, A. G., Carty, E., & Comellas, J. (2020) · Data in Brief · doi:10.1016/j.dib.2020.106059 · Cited by 27
Media Diet Homogeneity in a Fragmented Media Landscape
Young, D. G., & Anderson, K. (2017) · Atlantic Journal of Communication · doi:10.1080/15456870.2017.1251434 · Cited by 36
Chan, M. (2020) · Asian Journal of Communication · doi:10.1080/01292986.2020.1781219 · Cited by 32
Nelson, T. E. (2011) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780199545636.003.0012 · Cited by 32
Moralization and extremism robustly amplify myside sharing
Marie, A., Altay, S., & Strickland, B. (2023) · PNAS Nexus · doi:10.1093/pnasnexus/pgad078 · Cited by 32
Limbaugh's Social Media Nightmare: Facebook and Twitter as Spaces for Political Action
Warner, B. R., McGowen, S. T., & Hawthorne, J. (2012) · Journal of Radio & Audio Media · doi:10.1080/19376529.2012.722479 · Cited by 35
Blinded by the Spite? Path Model of Political Attitudes, Selectivity, and Social Media
Johnson, T. J., Kaye, B. K., & Lee, A. M. (2017) · Atlantic Journal of Communication · doi:10.1080/15456870.2017.1324454 · Cited by 35
Gauthier, J. F., & Graziano, L. M. (2018) · Journal of Crime and Justice · doi:10.1080/0735648x.2018.1472625 · Cited by 32
Edy, J. A., & Meirick, P. C. (2018) · Public Opinion Quarterly · doi:10.1093/poq/nfy043 · Cited by 32
Tang, G. K. Y., Hung, E. P. W., Au-Yeung, H.-K. C., & Yuen, S. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17020633 · Cited by 34
Tenenboim‐Weinblatt, K. (2009) · Political Communication · doi:10.1080/10584600903296960 · Cited by 32
Patterns of News Consumption in Austria: How Fragmented Are They?
Trilling, D., & Schönbach, K. (2013) · International journal of communication · Cited by 33
Lupia, A., Casey, L. S., Karl, K. L., Piston, S., Ryan, T. J., & Skovron, C. (2014) · Political Science Research and Methods · doi:10.1017/psrm.2014.12 · Cited by 31
Metadata
- Authors
- Iyengar, S., & Hahn, K. S.
- Affiliations
- Stanford University (US)
- University of California, Los Angeles (US)
- ORCID
- Iyengar, Shanto
- Venue
- Journal of Communication
- Publisher
- Oxford University Press (OUP)
- Published
- 2009-03
- Volume
- 59
- Issue
- 1
- Pages
- 19-39
- ISSN
- 0021-9916 (ISSN-L)
- 1460-2466
- OpenAlex
- W2166155258
- Cited by
- 1,940
- References
- 64
- Citations by year
- 2026: 73 · 2025: 137 · 2024: 116 · 2023: 105 · 2022: 167 · 2021: 156 · 2020: 246 · 2019: 162 · 2018: 148 · 2017: 129 · 2016: 101 · 2015: 92 · 2014: 89 · 2013: 80 · 2012: 64
- FWCI
- 148.28
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Communication (publishedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Media Influence and Politics
- Social Sciences › Communication › News Media Framing and Political Communication
- Social Sciences › Political Science and International Relations › Electoral Systems and Political Participation
- Keywords
- selective exposure, political affiliation, Fox News, convolutional neural networks, NPR, political polarization, political participation, new media
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