How emotions drive opinion polarization: An agent-based model

08/30/2019
by   Frank Schweitzer, et al.
0

We provide an agent-based model to explain the emergence of collective opinions not based on feedback between different opinions, but based on emotional interactions between agents. The driving variable is the emotional state of agents, characterized by their valence and their arousal. Both determine their emotional expression, from which collective emotional information is generated. This information feeds back on the dynamics of emotional states and of individual opinions in a non-linear manner. We derive the critical conditions for emotional interactions to obtain either consensus or polarization of opinions. Stochastic agent-based simulations and formal analyses of the model explain our results. Possible ways to validate the model are discussed.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
03/12/2020

An agent-based model of multi-dimensional opinion dynamics and opinion alignment

It is known that individual opinions on different policy issues often al...
research
08/24/2020

Enhanced or distorted wisdom of crowds? An agent-based model of opinion formation under social influence

We propose an agent-based model of collective opinion formation to study...
research
07/14/2020

A model to support collective reasoning: Formalization, analysis and computational assessment

Inspired by e-participation systems, in this paper we propose a new mode...
research
06/29/2020

An agent-based model of interdisciplinary interactions in science

An increased interdisciplinarity in science projects has been highlighte...
research
06/02/2020

Learning Opinion Dynamics From Social Traces

Opinion dynamics - the research field dealing with how people's opinions...
research
12/16/2020

Exploring Narrative Economics: An Agent-Based-Modeling Platform that Integrates Automated Traders with Opinion Dynamics

In seeking to explain aspects of real-world economies that defy easy und...
research
07/12/2022

Data-driven Control of Agent-based Models: an Equation/Variable-free Machine Learning Approach

We present an Equation/Variable free machine learning (EVFML) framework ...

Please sign up or login with your details

Forgot password? Click here to reset