The Impact of Artificial Intelligence on Intelligence Media Innovation: Evidence from Xiaohongshu Short-Video Platform in China
Authors
Faculty of Social Sciences and Humanities, Universiti Malaysia Sabah (Malaysia)
Faculty of Social Sciences and Humanities, Universiti Malaysia Sabah (Malaysia)
Faculty of Social Sciences and Humanities, Universiti Malaysia Sabah (Malaysia)
Academy of Arts and Creative Technology, Universiti Malaysia Sabah (Malaysia)
Article Information
DOI: 10.47772/IJRISS.2026.10200063
Subject Category: Social science
Volume/Issue: 10/2 | Page No: 834-843
Publication Timeline
Submitted: 2026-02-01
Accepted: 2026-02-09
Published: 2026-02-24
Abstract
This study investigates the impact of artificial intelligence (AI) on intelligence media innovation, using the Xiaohongshu short-video platform in China as an empirical case. As AI technologies increasingly reshape digital media ecosystems, intelligence media platforms rely on algorithmic systems to optimize content production, recommendation, user engagement, and business model development. Drawing on a questionnaire survey of 210 rofessionals within the Xiaohongshu ecosystem, including content creators, editorial staff, platform managers, and technical personnel, this study examines how AI is integrated into media workflows and how such integration contributes to innovation outcomes. The findings reveal that AI plays a pivotal role in driving intelligence media innovation across multiple dimensions. AI-assisted content production, automated tagging, trend analysis, and recommendation algorithms significantly enhance workflow efficiency and support data-driven creative decision-making. Moreover, AI-driven personalization strengthens user engagement by delivering customized content, increasing interaction, retention, and overall platform competitiveness. The results also indicate that AI analytics facilitate business model innovation by enabling targeted advertising, influencer collaborations, and e-commerce integration. Although some respondents express concerns regarding content homogenization and over-reliance on algorithms, the overall evidence suggests that AI functions as an effective enabler of innovation when combined with human creativity and oversight. his study contributes empirical insights into AI-enabled intelligence media innovation and provides practical implications for digital media platforms seeking sustainable and intelligent development.
Keywords
Artificial intelligence, intelligence media inovation, Xiaohongshu Short-Video
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References
1. Al Adwan, M. N., Mahmoud, M. A. A., Abdallah, R., Abokhoza, R., & Taha, S. (2023). The impact of artificial intelligence applications on media industries: a prospective study. Journal of Namibian Studies: History Politics Culture, 1(33), 721-734. [Google Scholar] [Crossref]
2. Ali, J. A. H., Gaffinet, B., Lezoche, M., Panetto, H., & Naudet, Y. (2025). Enabling human–CPS cognitive interoperability: Cognitive architectures as technologies for human-like cognitive digital twins. Journal of Industrial Information Integration, 103, 100969. [Google Scholar] [Crossref]
3. Baia, E., Ferreira, J. J., & Rodrigues, R. (2020). Value and rareness of resources and capabilities as sources of competitive advantage and superior performance. Knowledge Management Research & Practice, 18(3), 249-262. [Google Scholar] [Crossref]
4. Bao, F., Razi, S. A. B. H. M., & Yasin, M. A. I. B. (2024). A Case Study on the Transformation of Chinese Opera Radio under the Ecological Environment of Media Integration. Studies in Media and Communication, 12(1), 124-131. [Google Scholar] [Crossref]
5. Chan-Olmsted, S. M. (2019). A review of artificial intelligence adoptions in the media industry. International journal on media management, 21(3-4), 193-215. [Google Scholar] [Crossref]
6. Changkui, L. (2025). Cognitive Computing Models in Artificial Intelligence Education: From Theory to Practice. Artificial Intelligence Education Studies, 1(1), 1-22. [Google Scholar] [Crossref]
7. Duan, Y., Edwards, J. S., & Dwivedi, Y. K. (2019). Artificial intelligence for decision making in the era of Big Data–evolution, challenges and research agenda. International journal of information management, 48, 63-71. [Google Scholar] [Crossref]
8. Gavran, I., Honcharuk, S., Mykhalov, V., Stepanenko, K., & Tsimokh, N. (2025). The impact of artificial intelligence on the production and editing of audiovisual content. Preservation, Digital Technology & Culture, 54(3), 223-235. [Google Scholar] [Crossref]
9. Geissinger, A., Laurell, C., Öberg, C., & Sandström, C. (2023). Social media analytics for innovation management research: A systematic literature review and future research agenda. Technovation, 123, 102712. [Google Scholar] [Crossref]
10. Hanafizadeh, P., Barkhordari Firouzabadi, M., & Vu, K. M. (2021). Insight monetization intermediary platform using recommender systems. Electronic Markets, 31(2), 269-293. [Google Scholar] [Crossref]
11. Kandepu, R. K., & Harry, A. (2023). The rise of AI in content management: Reimagining intelligent workflows. American Journal of Engineering, Mechanics and Architecture, 1(7), 78-85. [Google Scholar] [Crossref]
12. Kim, E., Lee, D., Bae, K., & Rim, M. (2015). Developing and evaluating new ICT innovation system: case study of Korea's smart media industry. ETRI Journal, 37(5), 1044-1054. [Google Scholar] [Crossref]
13. Meena, M. R., Jingar, M. P., & Gupta, S. (2020). Artificial intelligence: A digital transformation tool in entertainment and media industry. Our Heritage, 68(1), 4661-4675. [Google Scholar] [Crossref]
14. Na, C., Kim, E., & Shin, K. (2019). Can user innovation grow a firm? The case of the Korean smart media industry. Electronics, 8(10), 1114. [Google Scholar] [Crossref]
15. Nasser El Erafy, A. (2023). Applications of Artificial Intelligence in the field of media. International Journal of Artificial Intelligence and Emerging Technology, 6(2), 19-41. [Google Scholar] [Crossref]
16. Nguyen, K. M., Nguyen, N. T., Ngo, N. T. Q., Tran, N. T. H., & Nguyen, H. T. T. (2024). Investigating consumers’ purchase resistance behavior to AI-Based content recommendations on short-video platforms: a study of greedy and biased recommendations. Journal of Internet Commerce, 23(3), 284-327. [Google Scholar] [Crossref]
17. Paquienseguy, F., & Guo, Q. (2025). Douyin and the digital spread of intangible cultural heritage: Transforming cultural dissemination in the short videos age. Emerging Media, 27523543251344976. [Google Scholar] [Crossref]
18. Rong, K., Huang, J., Hao, F., Xie, D., & Li, S. (2025). Copyright and Originality: Evidence from Short Video Creation in a Platform Market. Management and Organization Review, 4(1), 1-23. [Google Scholar] [Crossref]
19. Shafa, H. (2025). Artificial intelligence-driven business intelligence models for enhancing decision-making in us enterprises. ASRC Procedia: Global Perspectives in Science and Scholarship, 1(01), 771-800. [Google Scholar] [Crossref]
20. Sultana, R. (2025). Artificial Intelligence In Data Visualization: Reviewing Dashboard Design And Interactive Analytics For Enterprise Decision-Making. International Journal of Business and Economics Insights, 5(3), 01-29. [Google Scholar] [Crossref]
21. Sultana, R. (2025). Artificial Intelligence In Data Visualization: Reviewing Dashboard Design And Interactive Analytics For Enterprise Decision-Making. International Journal of Business and Economics Insights, 5(3), 01-29. [Google Scholar] [Crossref]
22. Zhai, Y., Yan, J., Zhang, H., & Lu, W. (2020). Tracing the evolution of AI: conceptualization of artificial intelligence in mass media discourse. Information discovery and delivery, 48(3), 137-149. [Google Scholar] [Crossref]
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