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Fundraising and vote distribution: A non-equilibrium statistical approach
Hygor P M Melo1,2, Nuno A M Araújo1,3,4, José S Andrade4
1Centro de Física Teórica e Computacional, Universidade de Lisboa, Lisboa, Portugal.
Plos One
|October 31, 2019
Summary
This study links campaign spending to election votes using Shannon entropy and Superstatistics. The framework helps predict election outcomes and detect potential campaign finance or vote-counting misconduct.
Area of Science:
- Computational Social Science
- Statistical Physics
Background:
- Campaign finance and vote counts are strongly correlated but not linearly related.
- Election outcomes are influenced by candidate numbers, voter demographics, and resource allocation.
Purpose of the Study:
- To develop a theoretical framework connecting campaign spending distributions to vote distributions.
- To create a tool for predicting election results and identifying potential electoral fraud.
Main Methods:
- Utilized Shannon entropy maximization and Superstatistics to model the relationship between money and votes.
- Applied the framework to real-world proportional election data involving thousands of candidates.
Main Results:
- Established a direct relationship between the statistical distributions of campaign expenditures and candidate votes.
- Demonstrated the framework's ability to predict election outcomes with high accuracy.
Conclusions:
- The developed model offers a novel approach to understanding campaign finance dynamics and electoral integrity.
- Significantly reduces the number of candidates requiring audits for potential misconduct, improving efficiency in election oversight.
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