Detecting “Ripples” of AI-Human Interaction: Three Social Media Cases

Abstract This study introduces an original concept—“social ripple”—to describe the social network effects of AI–Human Interaction that extend beyond the immediate interactants, and proposes a corresponding analytical framework. Three representative social media cases situated at distinct ripple levels—direct interaction, proximal interpersonal, and distant interpersonal—were selected. Using a mixed-methods approach, the study analyzed comment texts from these cases. The findings reveal that: (a) Cognitive Dimension: AI’s personalized response mechanisms generate a “paradox of emotional authenticity”—simultaneously fulfilling immediate affective needs while leading to persistent skepticism due to perceived “non-objectivity” and bias reinforcement. (b) Relational Dimension: The involvement of AI in intimate relationships creates “emotional competition,” where anthropomorphic feedback can destabilize bonds. (c) Societal Dimension: Distant publicsconstruct abstract values centered on “human–existence–emotion,” elevating the controversy over AI romance into a collective defense of human dignity and thereby redefining the essence of social distance—from physical or relational proximity to a distinction based on value positions.