Tower of Babel in Cross-Cultural Communication: A Case Study of #Give Me a Chinese Name# Dialogues During the "TikTok Refugees'' Event

2026-02-20

AI Summary

This study investigates the cross-cultural naming interactions between Western and Chinese users on Xiaohongshu following the influx of “TikTok refugees” in early 2025, focusing on the encoding–decoding challenges Western users encounter when requesting Chinese names from native speakers. Analyzing over 70,000 comments, the research develops a human–large language model collaborative in-the-loop analytical framework to systematically identify multi-layered cross-cultural encoding strategies and their combinatorial patterns. It introduces the novel concept of a “digital Tower of Babel” in cross-cultural naming, demonstrating how layered encoding strategies amplify decoding difficulty. The study further provides empirical evidence of a significant positive correlation between encoding complexity and user engagement metrics—such as likes—thereby addressing a critical gap in human–computer interaction research within multilingual and multicultural contexts.

Technology Category

• Humans and AI: Human-Computer Interaction
• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction
• Application Domains: Humanities & Computational Social Science

Application Category

• Economics, Online Markets and Human Computation: The sharing economy
• Web Mining and Content Analysis: Mining multimedia, multimodal, multilingual, cross-lingual Web data
• Search and Retrieval-Augmented AI: Multilingual and cross-lingual Web search

Abstract

The sudden influx of "TikTok refugees'' into the Chinese platform RedNote in early 2025 created an unprecedented, large-scale online cross-cultural communication event between the West and East. Although prior HCI research has studied user behavior in social media, most work remains confined to monolingual or single-cultural contexts, leaving cross-linguistic and cultural dynamics underexplored. To address this gap, we focused on a particularly challenging cross-cultural encoding-decoding task that remains stubbornly beyond the reach of machine translation, i.e., foreign newcomers asking Chinese users for Chinese names, and examined how people collectively constructed a digital "Babel Tower'' through various information encoding strategies. We collected and analyzed over 70,000 comments from RedNote with a creative human-in-the-loop approach using large language models, deriving a systematic framework summarizing cross-cultural information encoding strategies, how they are combined and layered to complicate decoding, and how they relate to engagement metrics such as the number of likes.

Problem

• cross-cultural communication
• machine translation
• information encoding
• social media
• TikTok refugees

Innovation

• cross-cultural communication
• human-in-the-loop
• large language models
• information encoding strategies
• machine translation limitations