Legislative Vote Prediction using Campaign Donations and Fuzzy Hierarchical Communities

Wahl, Scott; Sheppard, John W.; Shanahan, Elizabeth A.

doi:10.1109/icmla.2019.00129

Cited by 2 publications

(2 citation statements)

References 35 publications

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“…There are numerous techniques to assess political relationships within voting organizations based on the compilation of statistics from votes by members. Methods range from clustering techniques [1][2][3] and network analyses [3][4][5], to multi-dimensional scaling (MDS) [6][7][8] and dimensionality reduction [9][10][11][12]. These approaches seek to highlight, or define, where people or groups of people are most similar and most divergent in their political behaviors.…”

Section: Introductionmentioning

confidence: 99%

“…These approaches seek to highlight, or define, where people or groups of people are most similar and most divergent in their political behaviors. Applications include analysis and interpretation of historical voting data [4,[13][14][15], identification of voting coalitions among individuals [16][17][18][19], and prediction of future voting patterns [2,20]. Within one visualization it can be difficult to encompass or present a view of interesting or unique relationships of individuals relative to some larger group, each other, and other sub-groups, and interpretable quantitative information on the strength or proximity of these relationships is absent in the output from many methods [4,9,19,[21][22][23].…”

Section: Introductionmentioning

confidence: 99%

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The Split Senate

Chari

Pachter

2021

Preprint

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The theory of split systems provides a mathematical formalism for understanding and visualizing collections of partitions of sets into two parts. In particular, split networks, which generalize phylogenetic trees, are widely used in evolutionary biology. Here we show that these tools can be used to analyze and visualize voting patterns. As an example, we consider United States Senate votes, and we show that the Neighbor-Net algorithm, coupled to SplitsTree visualization, provides an effective exploratory data analysis framework for elucidating voting patterns among senators. We also introduce a statistical approach to identify voting patterns associated with specific groups of senators, and use it to study shifts in inter-and intra-party structures over time. The analyses we describe should be broadly applicable to visualizing and studying coalitions in any voting organization.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Split Senate

Chari

Pachter

2021

Preprint

View full text Add to dashboard Cite

show abstract

The Split Senate

Chari

Pachter

2021

Preprint

View full text Add to dashboard Cite

The theory of split systems provides a mathematical formalism for understanding and visualizing collections of partitions of sets into two parts. In particular, split networks, which generalize phylogenetic trees, are widely used in evolutionary biology. Here we show that these tools can be used to analyze and visualize voting patterns. As an example, we consider United States Senate votes, and we show that the Neighbor-Net algorithm, coupled to SplitsTree visualization, provides an effective exploratory data analysis framework for elucidating voting patterns among senators. We also introduce a statistical approach to identify voting patterns associated with specific groups of senators, and use it to study shifts in inter- and intra- party structures over time. The analyses we describe should be broadly applicable to visualizing and studying coalitions in any voting organization.

show abstract

Legislative Vote Prediction using Campaign Donations and Fuzzy Hierarchical Communities

Cited by 2 publications

References 35 publications

The Split Senate

The Split Senate

The Split Senate

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