# Media Environment, Dual Process and Polarization: A Computational Approach

## TL;DR

This paper models how media environments influence political polarization using a Bayesian network that combines motivated and analytic reasoning, showing polarization worsens in a post-truth context.

## Contribution

It introduces a novel computational model integrating dual reasoning theories to analyze media influence on polarization.

## Key findings

- Polarization increases in post-truth media environments
- Bayesian network effectively captures media influence dynamics
- Model highlights importance of truthfulness and alignment in media

## Abstract

News articles of varying degrees of truthfulness and political alignment, and their influences on the political opinions of the media consumers are modeled as a Bayesian network incorporating a mixture of ideas from dual-reasoning models of Motivated Reasoning and Analytic/Intuitive Reasoning. The result shows that as the media environment moves towards the Post-Truth world, the problem of political polarization becomes exacerbated.