Evaluating the Quality of Changes in Voter Registration Databases

Part of Special Symposium on Election Sciences

Bibliographic Data

ID6180288
AuthorsSeo-Young Silvia Kim (0000-0002-8801-9210, California Institute of Technology, corresponding author), Spencer Schneider (California Institute of Technology), R Michael Alvarez (0000-0002-8113-4451, California Institute of Technology)
Year2020
Volume48
Issue6
Pages670-676
Publication date2020-11-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueAmerican Politics Research (JOURNAL)
Journal identifiersISSN: 1532-673X • E-ISSN: 1552-3373
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1177/1532673x19870512
OpenAlexW3049363133
LanguageEN
Citations received4
References cited8

The administration of elections depends crucially upon the quality and integrity of voter registration databases. In addition, political scientists are increasingly using these databases in their research. However, these databases are dynamic and may be subject to external manipulation and unintentional errors. In this article, using data from Orange County, California, we develop two methods for evaluating the quality of voter registration data as it changes over time: (a) generating audit data by repeated record linkage across periodic snapshots of a given database and monitoring it for sudden anomalous changes and (b) identifying duplicates via an efficient, automated duplicate detection, and tracking new duplicates and deduplication efforts over time. We show that the generated data can serve not only to evaluate voter file quality and election integrity but also as a novel source of data on election administration practices

Audit · Business · Data deduplication · Data mining · Data quality · Database · Political science · Politics · Record linkage · Voter registration · Voting · Computer Science · Data Quality and Management · Internet Traffic Analysis and Secure E-voting · Privacy-Preserving Technologies in Data · Accounting

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