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.

翻译：2025年初，“TikTok难民”突然涌入中国平台RedNote，在东西方之间引发了一场前所未有的大规模在线跨文化传播事件。尽管先前的人机交互研究已探讨过社交媒体中的用户行为，但多数工作仍局限于单语或单一文化语境，对跨语言与跨文化动态的探索尚不充分。为填补这一空白，我们聚焦于一项机器翻译迄今仍难以应对的、极具挑战性的跨文化编码-解码任务——即外国新用户向中文用户请求中文名字——并考察了人们如何通过各种信息编码策略共同构建起一座数字“巴别塔”。我们采用一种结合大型语言模型的创造性人机协同方法，收集并分析了RedNote上超过70,000条评论，从而推导出一个系统性框架。该框架总结了跨文化信息编码策略、这些策略如何组合与叠加以增加解码难度，以及它们如何与点赞数等互动指标相关联。