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Research Article
Open Access

A Data-Driven Voter Guide for U.S. Elections: Adapting Quantitative Measures of the Preferences and Priorities of Political Elites to Help Voters Learn About Candidates

Adam Bonica
RSF: The Russell Sage Foundation Journal of the Social Sciences November 2016, 2 (7) 11-32; DOI: https://doi.org/10.7758/RSF.2016.2.7.02
Adam Bonica
aAssistant professor of political science at Stanford University. He is also co-founder at Crowdpac Inc
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RSF: The Russell Sage Foundation Journal of the Social Sciences: 2 (7)
RSF: The Russell Sage Foundation Journal of the Social Sciences
Vol. 2, Issue 7
1 Nov 2016
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A Data-Driven Voter Guide for U.S. Elections: Adapting Quantitative Measures of the Preferences and Priorities of Political Elites to Help Voters Learn About Candidates
Adam Bonica
RSF: The Russell Sage Foundation Journal of the Social Sciences Nov 2016, 2 (7) 11-32; DOI: 10.7758/RSF.2016.2.7.02

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A Data-Driven Voter Guide for U.S. Elections: Adapting Quantitative Measures of the Preferences and Priorities of Political Elites to Help Voters Learn About Candidates
Adam Bonica
RSF: The Russell Sage Foundation Journal of the Social Sciences Nov 2016, 2 (7) 11-32; DOI: 10.7758/RSF.2016.2.7.02
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  • Article
    • Abstract
    • DEMOCRATIZING POLITICAL DATA
    • DATA ARCHITECTURE
    • OVERALL MEASURES OF CANDIDATE IDEOLOGY
    • A MODEL TO MEASURE CANDIDATE PRIORITIES AND POSITIONS ACROSS ISSUES
    • A DATA-DRIVEN VOTER GUIDE
    • CONCLUSIONS
    • FOOTNOTES
    • REFERENCES
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  • References
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Keywords

  • ideal point estimation
  • text-as-data
  • supervised machine learning
  • voting advice applications

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