An Agent-Based Model of Collective Emotions in Online Communities

TL;DR

This paper presents an agent-based model to understand how collective emotions emerge in online communities through stochastic dynamics and feedback mechanisms, supported by simulations and analytical insights.

Contribution

It introduces a novel agent-based framework combining emotional valence and arousal with feedback from online communication to study collective emotions.

Findings

Conditions for bimodal valence distribution identified

Scenarios for one-time or repeated collective emotions characterized

Model provides testable hypotheses for online community data

Abstract

We develop a agent-based framework to model the emergence of collective emotions, which is applied to online communities. Agents individual emotions are described by their valence and arousal. Using the concept of Brownian agents, these variables change according to a stochastic dynamics, which also considers the feedback from online communication. Agents generate emotional information, which is stored and distributed in a field modeling the online medium. This field affects the emotional states of agents in a non-linear manner. We derive conditions for the emergence of collective emotions, observable in a bimodal valence distribution. Dependent on a saturated or a superlinear feedback between the information field and the agent's arousal, we further identify scenarios where collective emotions only appear once or in a repeated manner. The analytical results are illustrated by agent-based computer simulations. Our framework provides testable hypotheses about the emergence of collective emotions, which can be verified by data from online communities.