The Dynamics of Emotional Chats with Bots: Experiment and Agent-Based Simulations

TL;DR

This study explores how emotional chatbots influence user behavior and collective emotional dynamics through experiments and agent-based simulations, revealing persistent emotional fluctuations and clustering in online interactions.

Contribution

It introduces an experimental setup with emotional chatbots and employs agent-based modeling to analyze collective emotional behavior in online social networks.

Findings

Temporal correlations in emotional message time series

Persistent fluctuations and clustering by emotion

Agent-based simulations replicate observed emotional dynamics

Abstract

Quantitative research of emotions in psychology and machine-learning methods for extracting emotion components from text messages open an avenue for physical science to explore the nature of stochastic processes in which emotions play a role, e.g., in human dynamics online. Here, we investigate the occurrence of collective behavior of users that is induced by chats with emotional Bots. The Bots, designed in an experimental environment, are considered. Furthermore, using the agent-based modeling approach, the activity of these experimental Bots is simulated within a social network of interacting emotional agents. Quantitative analysis of time series carrying emotional messages by agents suggests temporal correlations and persistent fluctuations with clustering according to emotion similarity. {All data used in this study are fully anonymized.}