The “Mass-Energy” Dynamics of Academic Writing and the Ethical Implications of Generative Artificial Intelligence

Qu Yitong; Li Yuhai; Huang Xinyi

doi:10.13266/j.issn.0252-3116.2026.16.026

Library and Information Service >

2026 , Vol. 70 >Issue 16: 120 - 132

DOI: https://doi.org/10.13266/j.issn.0252-3116.2026.16.026

RESEARCH PAPERS

The “Mass-Energy” Dynamics of Academic Writing and the Ethical Implications of Generative Artificial Intelligence

Qu Yitong ,
Li Yuhai ,
Huang Xinyi

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1 School of Information Management, Central China Normal University, Wuhan 430079;
2 Research Center for Innovative Development of Chinese Libraries, Central China Normal University, Wuhan 430079;
3 School of Economics and Management, University of Science and Technology Beijing, Beijing 100083

Qu Yitong, Doctoral Candidate, E-mail: 18760307636@163.com; Li Yuhai, Professor, PhD, Doctoral Supervisor; Huang Xinyi, Doctoral Candidate.

Received date: 2025-06-25

Revised date: 2025-12-09

Online published: 2026-08-20

Supported by

This work is supported by the Fundamental Research Funds for the Central Universities titled “Research on the theory and method of knowledge organization of multi-perspective knowledge representation” (Grant No. CCNU24ZZ130).

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Abstract

[Purpose/Significance] The rapid emergence and iterative evolution of generative artificial intelligence have infused scientific research with substantial academic momentum, while simultaneously introducing complex ethical risks. By constructing feasible ethical pathways, this study aims to foster complementary strengths between AI and the humanities, mitigate excessive dependence on AI in scholarly writing, and enhance human–AI collaboration in academic contexts. [Method/Process] Drawing on 692 posts and 4 947 comments related to “AI writing” from the Xiaohongshu platform, this study employs high-frequency keyword co-occurrence analysis and LDA topic modeling. These results are further integrated with sentiment analysis using Chinese-BERT-wwm and semi-structured interviews with university students to uncover the challenges and dilemmas of applying generative AI in academic settings. [Result/Conclusion] Four high-attention topics are identified: intelligent assistance, writing quality, creative thinking, and academic norms. Sentiment analysis indicates that AI's intelligent assistance functions are broadly well-received; Attitudes toward AI writing quality are almost evenly split between positive and negative; concerns and opposition dominate perceptions of AI's impact on creative thinking; and negative sentiments slightly outweigh positive ones regarding academic norms. Clarifying the “mass-energy” of generative AI in academic writing is essential for transforming it into a powerful tool for knowledge presentation and the translation of scientific findings.

Key words： generative artificial intelligence; academic writing; application ethics

Cite this article

Qu Yitong , Li Yuhai , Huang Xinyi . The “Mass-Energy” Dynamics of Academic Writing and the Ethical Implications of Generative Artificial Intelligence[J]. Library and Information Service, 2026 , 70(16) : 120 -132 . DOI: 10.13266/j.issn.0252-3116.2026.16.026

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