AIAug 26, 2025

Wrong Face, Wrong Move: The Social Dynamics of Emotion Misperception in Agent-Based Models

arXiv:2509.00080v13 citationsh-index: 1
Originality Synthesis-oriented
AI Analysis

This research addresses the impact of emotion recognition biases on social processes, with implications for AI and psychology, though it is incremental as it applies existing methods to a new simulation context.

The study investigated how emotion misperception affects social dynamics in agent-based models, finding that low-accuracy emotion classifiers led to diminished trust, emotional disintegration into sadness, and disordered social organization, while high accuracy fostered resilient emotional clusters and cohesion.

The ability of humans to detect and respond to others' emotions is fundamental to understanding social behavior. Here, agents are instantiated with emotion classifiers of varying accuracy to study the impact of perceptual accuracy on emergent emotional and spatial behavior. Agents are visually represented with face photos from the KDEF database and endowed with one of three classifiers trained on the JAFFE (poor), CK+ (medium), or KDEF (high) datasets. Agents communicate locally on a 2D toroidal lattice, perceiving neighbors' emotional state based on their classifier and responding with movement toward perceived positive emotions and away from perceived negative emotions. Note that the agents respond to perceived, instead of ground-truth, emotions, introducing systematic misperception and frustration. A battery of experiments is carried out on homogeneous and heterogeneous populations and scenarios with repeated emotional shocks. Results show that low-accuracy classifiers on the part of the agent reliably result in diminished trust, emotional disintegration into sadness, and disordered social organization. By contrast, the agent that develops high accuracy develops hardy emotional clusters and resilience to emotional disruptions. Even in emotionally neutral scenarios, misperception is enough to generate segregation and disintegration of cohesion. These findings underscore the fact that biases or imprecision in emotion recognition may significantly warp social processes and disrupt emotional integration.

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