Election Outcomes Sandbox (RShiny)

An interactive Shiny app for exploring how different voting methods pick winners across varying voting distributions. Compare outcomes in 1-D and 2-D political spaces, tweak parameters, and inspect round-by-round dynamics.

Website: Election Outcomes Sandbox Shiny App

Features

• Voting systems
  • Plurality
  • Ranked-Choice Voting
  • Approval with adjustable distance threshold
  • Cardinal (Score) using spatial distance
  • Borda Count
• Scales: up to 20 candidates and 500 voters (2-D) or 8 candidates and 50 voters (1-D)
• Visuals:
  • Choose between 1-D and 2-D examples
  • Side-by-side layout: visual map of voter and candidate positions on the left, election results on the right
  • Modifiable approval thresholds for approval voting shown as circles (2-D) or brackets (1-D)
  • RCV: eliminated candidates are crossed out on maps; stacked composition bars show vote transfers
• Tables:
  • Voter Data: coordinates, distances to each candidate, full preference order, and an “Approves” column (comma-separated approved candidates; blank if none)
  • Results: per-method outcomes; counts + percentages
    • Cardinal shows numeric score only
    • RCV shows X for eliminated candidates in the final round snapshot
• Sampling nicety (1-D): voter and candidate x-positions are sampled with a minimum 2-notch separation to avoid overplotting of tick marks.
• Results explanations:
  • Explanations for the rules of each voting system.
  • Explains which candidate won and why for each voting system and show relevant statistical information for current election example.
• Remove candidates option:
  • Can remove specific candidates from the election to see how their presence/absence affects the election outcome for different voting systems.
• Scenarios:
  • Preset scenarios for examples of center squeeze, spoiler effect, mutual majority criterion, Condorcet cycle, and clone penality.
• Import/Export:
  • Save/load specific election configurations.
  • Easy to create custom elections with specific voter and candidate placements.
• Voting criterion assessment output:
  • Can toggle view to show voting criterion assessments within election example for the following criterions: Majority Winner, Majority Loser, Plurality Leader, Mutual Majority, Condorcet Winner, IIA

Requirements

• R (≥ 4.1 recommended)
• Packages: shiny, tidyverse, shinyjs, ggforce, cowplot, DT, later

install.packages(c("shiny","tidyverse","shinyjs","ggforce","cowplot","DT","later"))

Screenshots of App

#1.
1-D Election Example Using Plurality Voting.

#2.
2-D Election Example Using Ranked-Choice Voting.

#3.
2-D Election Example Using Ranked-Choice Voting and Showing Candidate Eliminations.

#4.
Example of Election Output Information with Voting System Results Table and Voting Criteria Assessment Table with Criteria Explanations.

#5.
2-D Election Example Using Approval Voting and Showing Approval Thresholds.

#6.
1-D Election Example Using Cardinal (Score) Voting.

#7.
Spoiler Effect Election Example.