Online communities often develop shared symbolic vocabularies that strengthen insider bonds but implicitly marginalize newcomers. On Chinese platforms, this dynamic is exemplified by “absurd language,” a style distinguished by irony, exaggeration, and local memes. While this form of expression fosters in-group intimacy, it creates significant cultural barriers for “Sino-digital non-natives.” This study investigates how AI can mediate cultural integration beyond mere translation. We developed an AI mediator integrating Chain-of-Thought (CoT) and Retrieval-Augmented Generation (RAG) to scaffold this journey. A mixed-methods evaluation (N=14) demonstrates significant improvements in comprehension accuracy over a baseline LLM. Crucially, our qualitative analysis reveals a novel five-stage model of cultural integration. This model charts the user's journey from peripheral observation to confident participation, detailing the AI's evolving role from “expert guide” to “creative collaborator.” Our findings illuminate the dynamics of agency and trust, offering a framework for designing AI as a catalyst for community integration.
ACM CHI Conference on Human Factors in Computing Systems