Date of Award

Spring 5-6-2024

Document Type

Honors Project

Degree Name

Bachelor of Science

Department

Computer Science

Department Chair or Program Director

Anewalt, Karen

First Advisor

Davies, Stephen

Second Advisor

Zeitz, Jessica

Third Advisor

Chandrasekar, Prashant

Major or Concentration

Computer Science

Abstract

Political candidates in a democracy articulate positions on the issues of the day, but they are also highly aware of voter sentiment on those issues, and tailor their campaigns accordingly as they seek to win elections. Voters, too, adjust their political opinions based on (among other things) interactions with others in their social network. I present an agent-based simulation that models this dynamic interplay between candidates and voters, in order to shed light on what outcomes candidates can expect to result from a policy of “chasing” votes. The voters in the simulation differ from one another in the decision procedure they use in choosing who to vote for – these voting algorithms are modeled on results from the political science literature about the different ways voters make decisions. The model can thus be used to experiment with a virtual electorate, to determine the conditions under which vote-chasing candidates gain an advantage or perhaps even cause the election outcome to be objectively irrational.

CI2elections.py (43 kB)

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