How Policies Influence Academia: Evolution and Influencing Factors Based on Knowledge Flow

Journal of Measurement and Evaluation

JME, Vol. 1, No. 1, 2026, pp.118-138.

Print ISSN: 3106-0463; Online ISSN: 3106-0471

Journal homepage: https://www.jmeacta.com 

DOI：Https://doi.org/10.64058/JME.26.1.07

How Policies Influence Academia: Evolution and Influencing Factors Based on Knowledge Flow

Yang Siluo, Chen Tianxiu, Li Longfei, Liu Xiaojuan, Jiang Zhengcong(translator)

Abstract: Existing studies rarely examine, at a fine-grained level, the specific effects generated when policy texts are cited by academic papers. This study aims to provide decision support for policymakers seeking to enhance policy influence and policy-to-knowledge translation efficiency, while offering academia a new perspective for understanding the diffusion of policy knowledge and promoting synergy between policy communication and knowledge innovation. Focusing on the academic dissemination of policy within policy–academia interactions, this study takes artificial intelligence (AI) policies and the academic papers citing them as samples. More than 4,000 sentence-level citation chains containing policy knowledge elements were extracted. Using citation analysis, the thematic evolution, diffusion characteristics, and influencing factors of differences in policy knowledge flow were examined from the perspective of knowledge diffusion. In thematic terms, policy topics such as AI education, AI ethics, and AI justice receive concentrated scholarly attention and citations, and thus constitute key channels through which policy affects academia. Analysis of differences in knowledge flow shows that the dissemination power of policy knowledge elements follows a long-tail distribution: a small number of policy elements exert substantial influence, whereas most have only limited impact. The major drivers of differences in knowledge flow include policy topic and the administrative level of the issuing body, while institutional co-authorship and the time lag of secondary citation also show potential associations. Temporally, policies generally trigger scholarly responses in the short term (usually within three years), although some also exhibit delayed resurgence in knowledge flow, often in connection with national strategies or industrial development. It is therefore recommended that future policy design emphasize thematic focus and inter-organizational coordination, innovate policy activation mechanisms, and renew policy communication approaches.

Keywords: citation analysis; policy text; knowledge diffusion; knowledge evolution; knowledge flow; influencing factors

Author Biographies: Yang Siluo, Ph.D., Professor, and Ph.D. Supervisor. Research interests: bibliometrics and science evaluation. Chen Tianxiu, Master's student. Research interests: scientometrics and science evaluation. Li Longfei, Doctoral student. Research interests: scientometrics and science evaluation. Liu Xiaojuan, Ph.D., Professor, and Ph.D. Supervisor. Research interests: informetrics and science evaluation. Jiang Zhengcong (translator), corresponding author, a Master's student at the School of Statistics and Data Science, Zhejiang Gongshang University, specializes in Socio-economic Statistics, E-mail: 2990012170@qq.com.

Received: 30 Jan 2026 / Revised: 09 Feb 2026 / Accepted: 21 Feb 2026 / Published online: 30 Apr 2026 / Print published: 30 May 2026.

This article is an English translation of the following Chinese article: Yang, S. L., Chen, T. X., Li, L. F., et al. (2025). How Policy Texts Influence Academia: An Analysis of Evolution and Influencing Factors Based on Knowledge Flow. Information Studies: Theory & Application, 48(12), 24-33. https://doi.org/10.16353/j.cnki.1000-7490.2025.12.003