Citation
Abstract
This study examines how Chinese state media organizations adjust their communication strategies on short video platforms when reporting on national policy initiatives. Focusing on the rural revitalization strategy, we analyze how two well-known traditional media outlets, People’s Daily and CCTV News, shape digital discourse on Douyin. We extract topic patterns and sentiment orientations from 445 rural revitalization videos using a computational approach combining Latent Dirichlet Allocation (LDA) topic modeling and StructBERT sentiment analysis. The results reveal different digital communication strategies: People’s Daily is dominated by positive emotions on all topics, while CCTV News adopts a more differentiated sentiment design, especially when dealing with poverty alleviation and rural livelihood issues. These results show how institutional identity influences digital storytelling strategies. The party newspaper (People’s Daily) focuses on ideological reinforcement, while the State Television Station (CCTV) strikes a balance between promoting political content and emotional resonance. This study contributes to the understanding of how traditional news organizations can exploit opportunities on specific platforms while maintaining their institutional role in the digital environment.
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Official URL or Download Paper: https://www.frontiersin.org/articles/10.3389/fcomm...
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Additional Metadata
| Item Type: | Article |
|---|---|
| Subject: | Communication |
| Subject: | Social Sciences (miscellaneous) |
| Divisions: | Faculty of Modern Language and Communication Institute for Social Science Studies |
| DOI Number: | https://doi.org/10.3389/fcomm.2026.1710629 |
| Publisher: | Frontiers Media SA |
| Keywords: | Bert sentiment analysis; Digital media discourse; Framing theory; Lda model; Rural revitalization |
| Sustainable Development Goals (SDGs): | SDG 1: No Poverty, SDG 8: Decent Work and Economic Growth, SDG 16: Peace, Justice and Strong Institutions |
| Depositing User: | Ms. Siti Radziah Mohamed@mahmod |
| Date Deposited: | 28 Apr 2026 01:57 |
| Last Modified: | 28 Apr 2026 01:57 |
| Altmetrics: | http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.3389/fcomm.2026.1710629 |
| URI: | http://psasir.upm.edu.my/id/eprint/124969 |
| Statistic Details: | View Download Statistic |
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