# Network Structure Explains the Impact of Attitudes on Voting Decisions

## TL;DR

This paper shows that the structure of attitude networks, especially their connectivity and central elements, explains how attitudes influence voting decisions, enabling better prediction of voting behavior.

## Contribution

It introduces a network model to predict voting behavior based on attitude connectivity and centrality, a novel approach in political psychology.

## Key findings

- More connected attitude networks have a stronger impact on voting.
- Central attitude elements exert the greatest influence on behavior.
- Predictive power of attitudes depends on network connectivity.

## Abstract

Attitudes can have a profound impact on socially relevant behaviours, such as voting. However, this effect is not uniform across situations or individuals, and it is at present difficult to predict whether attitudes will predict behaviour in any given circumstance. Using a network model, we demonstrate that (a) more strongly connected attitude networks have a stronger impact on behaviour, and (b) within any given attitude network, the most central attitude elements have the strongest impact. We test these hypotheses using data on voting and attitudes toward presidential candidates in the US presidential elections from 1980 to 2012. These analyses confirm that the predictive value of attitude networks depends almost entirely on their level of connectivity, with more central attitude elements having stronger impact. The impact of attitudes on voting behaviour can thus be reliably determined before elections take place by using network analyses.