Communications in Humanities Research ISSN: 2753-7072
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Research Article

The Cultural Phenomenon of TikTok Users Migrating to Xiaohongshu: Investigating Underlying Motivations via Machine Learning and Mixed-Methods Analysis

Xinyu DengTongji University* Jinchen ChiaZhejiang University Sijia WuCommunication University of China

* Corresponding author: [email protected]

Abstract

This study examines the phenomenon of “TikTok refugees” migrating to Xiaohongshu (RedNote) as a novel, affectively-driven form of digital cross-cultural adaptation. Moving beyond functionalist explanations for platform switching, we argue that this migration is primarily motivated by emotional responses to geopolitical pressures. Using a mixed-methods approach that integrates computational social science techniques—including MDCOR (Machine Driven Classification of Open-ended Responses) for thematic analysis and SENA (Sentiment and Emotion Network Analysis) for emotion detection—with qualitative interpretation, we analyse user discussions drawn from YouTube commentary concerning this migration. Results show that negative emotions (e.g., anxiety, frustration) regarding the potential TikTok ban were the main drivers for migration (H1 supported). Afterwards, migrants demonstrated a significant increase in positive emotions (e.g., joy, belonging) on Xiaohongshu, indicating successful affective adaptation (H2 supported). Discourse analysis highlighted a predominant preference for Berry’s integration strategy in acculturation, where users retain their original digital cultural identity while actively engaging with Xiaohongshu’s community (H3 supported). A positive correlation was also identified between users' emotional attitudes towards migration and their level of cultural engagement on the new platform (H4 supported). By combining computational social science with cross-cultural adaptation theory, this study emphasises the crucial role of affective factors in shaping digital migration and grassroots community formation within global social media ecosystems.

Keywords: Digital Migration; TikTok; Xiaohongshu (RedNote); Machine Driven Classification of Open-ended Responses (MDCOR); Sentiment and Emotion Network Analysis (SENA)
Published: December 31, 2025
DOI: 10.54254/2753-7064/2026.HT31073
Volume: CHR Vol.78
pp. 91-108
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