The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
The Market for News
Open accessAbstract
We investigate the market for news under two assumptions: that readers hold beliefs which they like to see confirmed, and that newspapers can slant stories toward these beliefs. We show that, on the topics where readers share common beliefs, one should not expect accuracy even from competitive media: competition results in lower prices, but common slanting toward reader biases. On topics where reader beliefs diverge (such as politically divisive issues), however, newspapers segment the market and slant toward extreme positions. Yet in the aggregate, a reader with access to all news sources could get an unbiased perspective. Generally speaking, reader heterogeneity is more important for accuracy in media than competition per se.
Overview
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
Verification
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.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
REMEMBERING: A STUDY IN EXPERIMENTAL AND SOCIAL PSYCHOLOGY
Bartlett, F. C., & Burt, C. (1933) · British Journal of Educational Psychology · doi:10.1111/j.2044-8279.1933.tb02913.x · Cited by 7,475
Lord, C. G., Ross, L., & Lepper, M. R. (1979) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.37.11.2098 · Cited by 4,583
Cited by
Social Media and Fake News in the 2016 Election
Allcott, H., & Gentzkow, M. (2017) · Journal of Economic Perspectives · doi:10.1257/jep.31.2.211 · Cited by 6,767
Iyengar, S., Sood, G., & Lelkes, Y. (2012) · Public Opinion Quarterly · doi:10.1093/poq/nfs038 · Cited by 2,996
Filter 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
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
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
Metadata
- Authors
- Mullainathan, S., & Shleifer, A.
- Venue
- American Economic Review
- Publisher
- American Economic Association
- Published
- 2005-08-01
- Volume
- 95
- Issue
- 4
- Pages
- 1031-1053
- ISSN
- 0002-8282 (ISSN-L)
- OpenAlex
- W3123401135
- Cited by
- 1,180
- References
- 2
- FWCI
- 122.26
- Type
- journal article
- Language
- en
- Open access
- green
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
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
