The dynamics of strategic voting: pathways to consensus and gridlock
Jonathan Engle, Bryce Morsky

TL;DR
This paper models how voters' preferences, beliefs, and social influences interact to determine whether elections reach consensus or gridlock, revealing tipping points and the impact of echo-chambers.
Contribution
It introduces a computational model capturing heterogeneous voter behaviors and social dynamics, highlighting factors that lead to consensus or gridlock in democratic elections.
Findings
Voters' initial strategies and randomness influence outcomes.
Social learning drives voters toward consensus or gridlock.
Moderate echo-chambers can promote consensus.
Abstract
The outcomes of democratic elections rest on individuals' decision-making that is driven by their varying preferences and beliefs. Individuals may prefer consensus to gridlock, or gridlock to consensus, and information may be fractured via echo-chambers. To understand the role of these factors in whether or not elections reach consensus, we develop and explore a computational model in which voters have varying party affiliations, preferences, beliefs, and voting strategies. Voters may change their voting strategies either by imitating others or reconsidering their strategy individually. Preferences are orderings of the following election outcomes: a voter's party winning a super-majority, the opposing party winning such a majority, and gridlock. Voters beliefs and decisions are shaped by their social networks, and thus are heterogeneous in the population. We observe a "tipping point"…
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Taxonomy
TopicsGame Theory and Applications
