科技情报研究2025，Vol.7Issue(4)：13-23,11.DOI:10.19809/j.cnki.kjqbyj.2025.04.002
基于BERTopic模型和语义功能的主题演化研究
Studying Topic Evolution Based on BERTopic Model and Semantic Function
摘要
Abstract
[Purpose/significance]Topic evolution analysis can help researchers quickly grasp the research hotspots and development trends of a discipline.However,existing topic models often overlook the semantic functions and struc-tures of texts during topic extraction,making it difficult to reveal the deeper patterns of disciplinary development.This paper proposes an integrated framework for topic evolution analysis that combines the BERTopic model with semantic functions,aiming to enrich and improve the methodological system of topic evolution research.[Method/process]Firstly,the BERTopic model is used to extract topics,obtaining the"Topic-Word"distribution.Next,a discourse parsing tool analyzes abstracts into five semantic function segments,resulting in the"Semantic Function-Word"distribution.Finally,the two distributions are mapped to obtain the"Topic-Semantic Function"distribution.This approach analyz-es topics from a semantic function perspective and explores the impact of semantic function distribution on topic evo-lution.[Result/conclusion]An empirical study in the field of library and information science shows that the semantic function distribution of a topic affects its research popularity.Topics oriented towards"Method"and"Objective"may continue to rise in the future,while topics oriented towards"Background"are relatively mature and may enter a de-cline phase.The proposed method provides a more granular and accurate analysis of discipline development dynam-ics,helping the academic community better understand the dynamic changes in research hotspots.关键词
主题演化/BERTopic模型/语义功能/主题识别Key words
topic evolution/BERTopic/semantic function/topic identification分类
社会科学引用本文复制引用
曲佳彬,王孟阳..基于BERTopic模型和语义功能的主题演化研究[J].科技情报研究,2025,7(4):13-23,11.基金项目
国家社会科学基金青年项目"学术大数据背景下科学论文的论证结构抽取及应用研究"(编号:20CTQ009) （编号:20CTQ009）
