Rejection or Inclusion in the Emotion-Identity Dynamics of TikTok Refugees on RedNote

• URL: http://arxiv.org/abs/2507.14623v1
• Date: Sat, 19 Jul 2025 13:38:33 GMT
• Title: Rejection or Inclusion in the Emotion-Identity Dynamics of TikTok Refugees on RedNote
• Authors: Mingchen Li, Wenbo Xu, Wenqing Gu, Yixuan Xie, Yao Zhou, Yunsong Dai, Cheng Tan, Pan Hui,
• Abstract summary: This study examines cross-cultural interactions between Chinese users and self-identified "TikTok Refugees"<n>Based on a dataset of 1,862 posts and 403,054 comments, we use large language model-based sentiment classification and BERT-based topic modelling.
• Score: 20.87350224458745
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This study examines cross-cultural interactions between Chinese users and self-identified "TikTok Refugees"(foreign users who migrated to RedNote after TikTok's U.S. ban). Based on a dataset of 1,862 posts and 403,054 comments, we use large language model-based sentiment classification and BERT-based topic modelling to explore how both groups engage with the TikTok refugee phenomenon. We analyse what themes foreign users express, how Chinese users respond, how stances (Pro-China, Neutral, Pro-Foreign) shape emotional expression, and how affective responses differ across topics and identities. Results show strong affective asymmetry: Chinese users respond with varying emotional intensities across topics and stances: pride and praise dominate cultural threads, while political discussions elicit high levels of contempt and anger, especially from Pro-China commenters. Pro-Foreign users exhibit the strongest negative emotions across all topics, whereas neutral users express curiosity and joy but still reinforce mainstream discursive norms. Cross-topic comparisons reveal that appearance-related content produces the most emotionally balanced interactions, while politics generates the highest polarization. Our findings reveal distinct emotion-stance structures in Sino-foreign online interactions and offer empirical insights into identity negotiation in transnational digital publics.

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