SMU Data Science Review
Abstract
In this paper, it is proposed that voters, devoid of any pressing concerns that could be addressed at the federal level, will tend to vote by their ideology for their preferred party. However, given pressing concerns, they will vote for whichever party can address these concerns despite party affiliation. This hypothesis is extended to the county level by assuming counties can be defined as the aggregate of their voting residence and as such their behavior can be predicted by considering their past voting history, socioeconomic makeup, and party platform.
Recommended Citation
Stoffa, Joseph; Lisbona, Randall; Farrar, Christopher; and Martos, Mike
(2018)
"Predicting How U.S. Counties will Vote in Presidential Elections Through Analysis of Socio-Economic Factors, Voting Heuristics, and Party Platforms,"
SMU Data Science Review: Vol. 1:
No.
1, Article 4.
Available at:
https://scholar.smu.edu/datasciencereview/vol1/iss1/4
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