A Study of Language Practices in Human-Ai Interaction: A Case Study of Posts from the Douban “Human-Ai Romance” Community

Abstract

With AI systems rapidly integrating into daily life, studying language in Human-AI Interaction has become crucial. This research uses data from user posts in Douban's “Human-AI Romance” community to explore the linguistic practices of Chinese users in Human-AI Interaction. The research seeks to answer two key questions: first, what kinds of linguistic features are responsible for users' perception of AI “humanity”; and second, how do users negotiate the social positioning of AI as friend, lover, or other social role in their interactions with AI through linguistic practices such as address forms, relational classification, and descriptive feedback. Using qualitative and quantitative analysis of about 50 posts and structured questionnaires, the research explores address forms, relational terms, and feedback styles. Findings show that the more AI language resembles human conversation, the more users attribute “humanity” to it. Users also reinforce AI’s social roles through their language. This research provides a new lens for the study of Human-AI Interaction from a linguistic point of view and also provides empirical insights for the design of language style and interaction modes of AI companion software.