Psychological decoupling in responses to AI: emotional reactivity and behavioral discourse in digital environments

Artificial intelligence (AI) has become increasingly visible in digitally mediated environments, raising important questions about how users express emotional reactions to perceived AI presence. While prior research has frequently examined AI acceptance, trust, and behavioral outcomes, less is known about how different forms of AI perception are reflected in large-scale user-generated discourse. This study investigates the relationship between multidimensional AI perception, emotional expression, trust-related discourse, and purchase-related discourse in naturalistic online environments.

A large-scale dataset consisting of 2,326,781 cleaned YouTube comments collected from 8,947 videos and 5,176 channels was analyzed. AI perception was operationalized through six categories: automation perception, robotic communication style, scriptedness, lack of authenticity, perceived artificiality, and uncanny valley perception. The analytical pipeline combined LLM-assisted weak supervision, transformer-based classification, manual validation, sentiment analysis, and statistical association tests to examine emotional expression and discourse patterns across AI perception categories.

AI perception was highly prevalent throughout the dataset and was strongly associated with negative emotional expression. Comments containing AI perception cues exhibited substantially higher levels of negative sentiment than comments without such cues. Emotional expression varied meaningfully across AI perception categories, with robotic communication style, lack of authenticity, automation perception, and uncanny valley perception showing the highest levels of negative expression. In contrast, trust-related discourse and purchase-related discourse remained rare across the corpus and displayed only limited differentiation across AI perception conditions. These findings indicate that emotional expression is considerably more visible and differentiated than explicit behavioral discourse in AI-related user comments.

The findings support a pattern of expressive decoupling, whereby perceived AI presence is strongly reflected in emotional expression while explicit trust-related and purchase-related discourse remains sparse. Rather than indicating actual behavioral outcomes, the results suggest that AI-related perceptions primarily manifest as discursive emotional reactions within AI-saturated digital environments. The study contributes to digital mental health and human-AI interaction research by demonstrating how large-scale user-generated discourse can reveal psychologically meaningful patterns of emotional expression associated with perceived AI presence.