基于BERTopic主题模型的数据要素价值化热点主题及演化分析

陈婉铭; 刘媛华

doi:10.13266/j.issn.2095-5472.2025.037

PDF(3095 KB)

知识管理论坛 ›› 2025, Vol. 10 ›› Issue (6) : 553-564. DOI: 10.13266/j.issn.2095-5472.2025.037 CSTR: 32306.14.CN11-6036.2025.037

研究论文

基于BERTopic主题模型的数据要素价值化热点主题及演化分析

陈婉铭 ,
刘媛华

作者信息 +

Hot Topics and Evolution Analysis of Data Element Valorization Based on the BERTopic Model

Author information +

文章历史 +

摘要

【目的/意义】运用BERTopic主题模型分析我国数据要素价值化领域的核心主题、演化路径与前沿动态，为深化理论探索和指导实践应用提供宏观视角与客观依据。【方法/过程】以中国知网（CNKI）2019年至今收录的1 735篇文献为样本，采用BERTopic主题建模方法展开研究。首先通过预训练语言模型构建语义嵌入空间，并结合UMAP降维与HDBSCAN密度聚类算法，初步生成语义相近的主题簇。在此基础上，采用c-TF-IDF进行关键词加权，继而引入时序分析方法，追踪研究主题的动态演变规律。【结果/结论】研究发现：①当前研究主题聚焦于“企业创新与数据要素市场培育”“数据基础制度与产业数字化转型”“要素市场化配置与体制改革”“数据交易制度与市场竞争机制”和“数据赋能生产率提升与监管平衡”五大主题；②数据要素价值化呈现多维度协同特征，并形成动态演进机制。

Abstract

[Purpose/Significance] This study employs the BERTopic model to analyze the core themes, evolutionary pathways, and frontier dynamics of data element valorization in China, providing a macro perspective and objective foundation for advancing theoretical exploration and guiding practical applications. [Method/Process] Having used 1735 articles published in CNKI from 2019 to the present as the dataset, this research had applied the BERTopic topic modeling approach. First, a semantic embedding space had been constructed using a pre-trained language model, and UMAP had been applied for dimensionality reduction, combined with HDBSCAN for density-based clustering, to have initially generated the incorporation of a temporal analysis method to trace the dynamic evolution of research topics. [Result/Conclusion] The findings reveal that: ① Current research themes focus on five key areas: "Enterprise Innovation and Data Element Market Cultivation", "Data Infrastructure Systems and Industrial Digital Transformation", "Element Marketization Allocation and Institutional Reform", "Data Transaction Systems and Market Competition Mechanisms", and "Data Empowerment for Productivity Improvement and Regulatory Balance". ② Data element valorization exhibits multidimensional collaborative characteristics and forms a dynamic evolutionary mechanism.

导出引用

陈婉铭 , 刘媛华. 基于BERTopic主题模型的数据要素价值化热点主题及演化分析[J]. 知识管理论坛. 2025, 10(6): 553-564 https://doi.org/10.13266/j.issn.2095-5472.2025.037

Chen Wanming , Liu Yuanhua. Hot Topics and Evolution Analysis of Data Element Valorization Based on the BERTopic Model[J]. Knowledge Management Forum. 2025, 10(6): 553-564 https://doi.org/10.13266/j.issn.2095-5472.2025.037

中图分类号： G203

参考文献

列表( 原文顺序 | 文献年度倒序 | 文中引用次数倒序 ) 可视化分析

[1]

吴江, 陶成煦. 激活数据要素赋能千行万业——《“数据要素×”三年行动计划(2024—2026年)》政策解读[J]. 情报理论与实践, 2024, 47(3): 16-19.

, TAO

C X

. Activating data elements empowers thousands of businesses: policy interpretation of "the 'Data Elements x' Three-year Action Plan(2024-2026)" [J]. Information studies: theory & application, 2024, 47(3): 16-19.

本文引用 [1]

[2]	李海舰, 赵丽. 数据成为生产要素: 特征、机制与价值形态演进[J]. 上海经济研究, 2021(8): 48-59. LI H J, ZHAO L. Data becomes a factor of production: characteristics, mechanisms, and the evolution of value form [J]. Shanghai journal of economics, 2021(8): 48-59. 本文引用 [1]

[3]	张继栋. 地方国有企业数字化转型路径探讨[J]. 现代管理科学, 2021(3): 96-102. ZHANG J D. Practical suggestions and approaches for digital transformation of local stateowned enterprises[J]. Modern management science, 2021(3): 96-102. 本文引用 [1]

[4]	刘尚希, 邢丽, 樊轶侠, 等. 以数字化引领数实融合的内在机理与现实思考[J]. 财政研究, 2023, (12): 3-15. LIU S X, XING L, FAN Y X, et al. The inner mechanism and realistic thinking of digitalization leading the integration of digital economy and real economy[J]. Public finance research, 2023(12): 3-15.

[5]	俞伯阳, 丛屹. 数字经济、人力资本红利与产业结构高级化[J]. 财经理论与实践, 2021, 42(3): 124-131. YU B Y, CONG Y. Digital economy, human capital dividends, and advanced industrial structure[J]. The theory and practice of finance and economics, 2021, 42(3): 124-131.

[6]	尹西明, 林镇阳, 陈劲, 等. 数据要素价值化动态过程机制研究[J]. 科学学研究, 2022, 40(2): 220-229. YIN X M, LIN Z Y, CHEN J, et al. Research on the dynamic value creation process of data element [J]. Studies in science of science, 2022, 40(2): 220-229. 本文引用 [1]

[7]	柳卸林, 董彩婷, 丁雪辰. 数字创新时代：中国的机遇与挑战[J]. 科学学与科学技术管理, 2020, 41(6): 3-15. LIU X L, DONG C T, DING X C. Innovation in the digital world: the opportunities and challenges of China [J]. Science of science and management of S.& T., 2020, 41(6): 3-15. 本文引用 [1]

[8]	刘业政, 孙见山, 姜元春, 等. 大数据的价值发现：4C模型[J]. 管理世界, 2020, 36(2): 129-138. LIU Y Z, SUN J S, JIANG Y C, et al. 4C model: value discovery in big data [J]. Journal of management world, 2020, 36(2): 129-138.

[9]	何伟. 激发数据要素价值的机制、问题和对策[J]. 信息通信技术与政策, 2020(6): 4-7. HE W. Mechanism, problems and countermeasures to stimulate the value of data [J]. Information and communications technology and policy, 2020(6): 4-7. 本文引用 [1]

[10]	杨思洛, 吴丽娟. 基于BERTopic模型的国外信息资源管理研究进展分析[J]. 情报理论与实践, 2024, 47(2): 189-197. YANG S L, WU L J. Research progress of foreign information resource management: an analysis based on the BERTopic model[J]. Information studies: theory & application, 2024, 47(2): 189-197. 本文引用 [1]

[11]	苏会灵. 档案数据要素流通的关键问题与对策研究[J]. 山西档案, 2024(2): 62-64. SU H L. Research on key issues and countermeasures of archival data element circulation [J]. Shanxi archives, 2024(2): 62-64. 本文引用 [1]

[12]	CHEN C L P, ZHANG C Y. Data-intensive applications, challenges, techniques and technologies: a survey on big data [J]. Information sciences, 2014(275):314-347. 本文引用 [1]

[13]	CHEN M, MAO S, LIU Y. Big data: a survey[J].Mobile networks & applications, 2014, 19(2):171-209. 本文引用 [1]

[14]	CHEN P. Visualization of real-time monitoring datagraphic of urban environmental quality [J]. EURASIP journal on image and video processing, 2019, 42: 1-9. 本文引用 [1]

[15]	黄科满, 杜小勇. 数据治理价值链模型与数据基础制度分析[J]. 大数据, 2022, 8(4): 3-16. HUANG K M, DU X Y. Value chain model of data governance and its application on data governance regulation analysis [J]. Big data research, 2022, 8(4): 3-16. 本文引用 [1]

[16]	徐蔼婷, 宋妙缘. 基于“价值创造—实现”路径的数据要素核算问题研究[J]. 现代经济探讨, 2024(4): 13-21. XU A T, SONG M Y. Research on data factor accounting based on the path of "value formation and release" [J]. Modern economic research, 2024(4): 13-21. 本文引用 [1]

[17]	金骋路, 陈荣达. 数据要素价值化及其衍生的金融属性：形成逻辑与未来挑战[J]. 数量经济技术经济研究, 2022, 39(7): 69-89. JIN C L, CHEN R D. Data valuations and its derived financial attributes: formation logic and future challenges [J]. Journal of quantitative & technological economics, 2022, 39(7): 69-89. 本文引用 [1]

[18]	刘桂锋, 吴雅琪, 韩牧哲, 等. 面向数据要素价值化的数据资源应用场景创新研究[J]. 情报理论与实践, 2025, 48(1): 53-62. LIU G F, WU Y Q, HAN M Z, et al. Research on the innovation of data resource application scenarios oriented to the valorization of data elements [J]. Information studies: theory & application, 2025, 48(1): 53-62. 本文引用 [1]

[19]	GROOTENDORST M. BERTopic: neural topic modeling with a class-based TF-IDF procedure[J]. arXiv preprint, 2022, arXiv:2203.05794. 本文引用 [1]

[20]	张敏, 沈嘉裕. 突发公共卫生事件中政务短视频主题与用户行为的关联演化研究[J]. 情报杂志, 2023, 42(3): 181-189. ZHANG M, SHEN J Y. Research on the evolution of the association between governmental short video themes and user behavior in public health emergency[J]. Journal of intelligence, 2023, 42(3): 181-189. 本文引用 [1]

[21]	DEVLIN J, CHANG M W, LEE K, et al. BERT: pre-training of deep bidirectional transformers for language understanding[J]. arXiv preprint, 2018, arXiv:1810.04805. 本文引用 [1]

[22]	EGGER R, YU J. A topic modeling comparison between LDA, NMF, Top2Vec, and BERTopic to demystify Twitter posts[J]. Frontiers in sociology, 2022, 7: 886498.

[23]	HENDRY D, DARARI F, NURFADILLAH R, et al. Topic modeling for customer service chats[C]//2021 International conference on advanced computer science and information systems(ICACSIS). Depok: IEEE, 2021: 1-6.

[24]	KIM R, KIM D. Research trends of COVID-19 in public administration and policy research studies using BERTopic topic modeling [J]. Institute of governmental studies, 2022, 28(3): 105-137. 本文引用 [1]

[25]	张清慧, 陈谊, 武彩霞. 基于词表示模型的领域文献数据可视分析方法[J]. 图学学报, 2022, 43(4): 685-694. ZHANG Q H, CHEN Y, WU C X. A visual analysis approach for domain literature data based on word representation model [J]. Journal of graphics, 2022, 43(4): 685-694. 本文引用 [1]

[26]	刘洋, 柳卓心, 金昊, 等. 基于BERTopic模型的用户层次化需求及动机分析——以抖音平台为例[J]. 情报杂志, 2023, 42(12): 159-167. LIU Y, LIU Z X, JIN H, et al. User hierarchical need and motivation analysis ased on BERTopic model: taking Douyin platform as an example [J]. Journal of intelligence, 2023, 42(12): 159-167. 本文引用 [1]