The DOI matches its Crossref record.
Validation: What Big Data Reveal About Survey Misreporting and the Real Electorate
Open accessAbstract
Social scientists rely on surveys to explain political behavior. From consistent overreporting of voter turnout, it is evident that responses on survey items may be unreliable and lead scholars to incorrectly estimate the correlates of participation. Leveraging developments in technology and improvements in public records, we conduct the first-ever fifty-state vote validation. We parse overreporting due to response bias from overreporting due to inaccurate respondents. We find that nonvoters who are politically engaged and equipped with politically relevant resources consistently misreport that they voted. This finding cannot be explained by faulty registration records, which we measure with new indicators of election administration quality. Respondents are found to misreport only on survey items associated with socially desirable outcomes, which we find by validating items beyond voting, like race and party. We show that studies of representation and participation based on survey reports dramatically misestimate the differences between voters and nonvoters.
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
Cited by
Birds of the Same Feather Tweet Together. Bayesian Ideal Point Estimation Using Twitter Data
Barbera, P. (2012) · doi:10.2139/ssrn.2108098 · Cited by 983
Birds of the Same Feather Tweet Together: Bayesian Ideal Point Estimation Using Twitter Data
Barberá, P. (2015) · Political Analysis · doi:10.1093/pan/mpu011 · Cited by 982
Geographic Boundaries as Regression Discontinuities
Keele, L. J., & Titiunik, R. (2015) · Political Analysis · doi:10.1093/pan/mpu014 · Cited by 391
Meng, X.-L. (2018) · The Annals of Applied Statistics · doi:10.1214/18-aoas1161sf · Cited by 316
Ansolabehere, S., & Rivers, D. (2013) · Annual Review of Political Science · doi:10.1146/annurev-polisci-022811-160625 · Cited by 257
Self-citationDifferential Registration Bias in Voter File Data: A Sensitivity Analysis Approach
Nyhan, B., Skovron, C., & Titiunik, R. (2017) · American Journal of Political Science · doi:10.1111/ajps.12288 · Cited by 68
The Differential Effects of Economic Conditions and Racial Attitudes in the Election of Donald Trump
Green, J., & McElwee, S. (2018) · doi:10.31235/osf.io/un782 · Cited by 58
Testing the Participation Hypothesis: Evidence from Participatory Budgeting
Johnson, C., Carlson, H. J., & Reynolds, S. (2023) · Political Behavior · doi:10.1007/s11109-021-09679-w · Cited by 46
Keiding, N., & Louis, T. A. (2018) · Annual Review of Statistics and Its Application · doi:10.1146/annurev-statistics-031017-100127 · Cited by 36
A Bigger Pie: The Effects of High-Speed Internet on Political Behavior
Lelkes, Y. (2020) · Journal of Computer-Mediated Communication · doi:10.1093/jcmc/zmaa002 · Cited by 33
Metadata
- Authors
- Ansolabehere, S., & Hersh, E.
- Venue
- Political Analysis
- Publisher
- Cambridge University Press (CUP)
- Published
- 2012
- Volume
- 20
- Issue
- 4
- Pages
- 437-459
- ISSN
- 1047-1987 (ISSN-L)
- 1476-4989
- OpenAlex
- W2103972398
- Cited by
- 416
- References
- 0
- FWCI
- 67.67
- Type
- journal article
- Language
- en
- Open access
- bronze
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.