Audience perception and decoding of Chinese cultural content in global cross-media context based on LLM-enhanced temporal topic modeling
Bibliographic Data
| ID | 22092554 |
|---|---|
| Authors | Ru Xu (0000-0002-5203-5980, Southwestern University of Finance and Economics), Hongqing Guo (Southwestern University of Finance and Economics), Kai Wu (0000-0003-4684-9758, Southwestern University of Finance and Economics), Yue Zhuang (0000-0002-6058-3151, Southwestern University of Finance and Economics), Maojun Zhou (Wuhan University) |
| Year | 2026 |
| Volume | 11 |
| Publication date | 2026-06-05 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Communication (JOURNAL) |
| Journal identifiers | ISSN: 2297-900X • E-ISSN: 2297-900X |
| Publisher | Frontiers Media SA (PUBLISHER • CH) |
| DOI | 10.3389/fcomm.2026.1850055 |
| OpenAlex | W7163641438 |
| Language | EN |
| References cited | 10 |
Methodological limitations in cross-cultural social media research—temporal blindness, semantic misalignment, and data sparsity—constrain understanding of how global audiences decode Chinese cultural content. This study integrates Large Language Models with temporally-weighted topic modeling to examine non-Chinese audience reception of Chinese cultural videos on YouTube within an algorithmically-mediated environment. Using an LLM-enhanced Seeded-LDA model (k = 11), we analyzed 24,847 non-Chinese comments from high-engagement videos (2014–2025). DeepSeek-v4-flash facilitated multilingual preprocessing, comment filtering, and sentiment analysis. Temporal evolution was tracked via Dynamic Topic Modeling, and reply-thread networks were analyzed to detect politicization spillover. Eleven topics emerged, organized into four decoding positions: algorithmic empathy (travel and food content, >60% positive), value friction, civilizational comparison, and ideological contestation (narrative framing, >50% negative). Network analysis revealed platform-mediated politicization spillover in one-third of high-engagement threads. Three temporal regimes were identified: aesthetic curiosity (2014–2018), polarization (2018–2022), and complex bifurcation (2023–2025). Platform affordances and source attribution cues appear systematically linked to divergent decoding patterns, with self-media triggering empathetic responses and official media activating ideological contestation. The proposed computational framework advances large-scale analysis of platform-mediated cultural communication, though observational constraints limit causal claims
Affordance · Attribution · Conversation · Decoding methods · Ideology · Interactivity · Perception · Topic model · Asian Culture and Media Studies · Computational and Text Analysis Methods · Media Influence and Health
The Platform Society
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Leveraging large language models for thematic analysis
Applying LDA Topic Modeling in Communication Research
Exploring Cultural Meaning Construction in Social Media
| Highly cited | No |
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