ExpressionCueLens: A Cross-Cultural Analysis of Human-AI Companion Conversations on Social Media

2026-07-15

AI Summary

This study investigates how users across different cultural contexts perceive AI companions as agentic social partners and examines the anthropomorphic expressions in their language. To this end, we introduce ExpressionCueLens, the first systematic framework for categorizing anthropomorphism through ten cue types organized along four dimensions: linguistic, cognitive, behavioral, and perceptual. Applying a cross-platform mixed-methods approach, we analyze approximately 3,500 posts from Reddit and Xiaohongshu, combining iterative expert annotation with large language model–assisted labeling. Our findings reveal that Xiaohongshu users tend to express emotional vulnerability and rely more on non-perceptual cues, whereas Reddit users frequently employ temporal and embodied perceptual cues. These patterns demonstrate that cultural background and platform norms significantly shape human attributions of agency to AI, offering empirical grounding for the design of culturally sensitive AI companions.

Abstract

LLM-based AI companion agents are increasingly being perceived not only as tools but also as social companions. On social media, people recount conversations where these agents comfort, negotiate and assert boundaries, reflecting a growing attribution of human-like qualities. To profile how agency is perceived in human-AI (HAI) interactions, we introduce the ExpressionCueLens framework, which organizes linguistic, cognitive, behavioral and perceptual cues into ten categories of anthropomorphism expressions. We apply this framework to $\sim$3500 Reddit and XiaoHongShu posts that discuss HAI companionship. Through iterative expert annotation and LLM-assisted labeling, our cross-platform analysis indicates patterns consistent with the hypothesis that XiaoHongShu users use significantly more expressions of vulnerability and emotions, and more non-perceptual cues. Reddit users employ more perceptual cues with temporality and embodiment expressions. These findings suggest that cultural and platform norms shape the way that companion agents are treated as active, agentic partners, and provides design implications for culturally sensitive HAI companion agents.

Problem

• human-AI companionship
• anthropomorphism
• cross-cultural analysis
• social media
• agency perception

Innovation

• ExpressionCueLens
• anthropomorphism
• cross-cultural analysis
• human-AI companionship
• LLM-assisted labeling