Computational Modeling Reveals How Navigation Strategy and Ballot Layout Lead to Voter Error

Date
2020-09-16
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Abstract

Bad ballot design has affected the outcome of multiple elections in the United States. In order to build an automated tool for evaluation of ballots for potential usability problems, a range of voting behaviors on different ballot layouts have to be understood and modeled. The current studies are focussed on full-face paper ballots. Study 1 is an eye-tracking study. The ways that voters seek information on a full-face paper ballot was examined and the insights from the analysis results were integrated into Study 2. Study 2 is a cognitive modeling study. A family of 160 voting strategies were modeled using ACT-R to investigate how errors arise from the interaction of strategy and ballot design. The model was then validated by testing on a well-known bad ballot: the ballot from Kewaunee County, Wisconsin 2002. The Wisconsin error was reproduced successfully.

Description
Degree
Master of Arts
Type
Thesis
Keywords
voting, ballot layout, usability, ACT-R, computational modeling
Citation

Wang, Xianni. "Computational Modeling Reveals How Navigation Strategy and Ballot Layout Lead to Voter Error." (2020) Master’s Thesis, Rice University. https://hdl.handle.net/1911/109363.

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