QIU Jiaxuan, LIU Jiajing, ZHENG Jianming
LIBRARY TRIBUNE.
2024, 44(9):
16-27.
In order to fully understand the research progress in the field of Library and Information Science (LIS) in China in 2023,and to reveal the research patterns and hotspots,this article applies Python to perform word cloud visualization analysis and topic extraction of the papers published in CSSCI source journals in the field of LIS in 2023. Using CiteSpace,a bibliometric tool,a co-occurrence knowledge graph of high-frequency keywords is introduced to explore the research topics in a mutually verifiable way. Using a deep learning based Sentence-BERT+UMAP+K-means+C-TF-IDF model,topics are identified and clustered,resulting in 39 research topics. The topics are manually refined into labels and categorized into four primary themes and fifteen secondary themes:public culture (librarianship,public digital culture),intelligence system (national security intelligence,competitive intelligence,emergency intelligence,academic intelligence,intelligence analysis technology),data governance (data flow regulation,data use security,research data governance,government data openness),and information behavior (information needs,information seeking behavior,information adoption behavior,information dissemination behavior). Through interpretative content analysis,the study systematically reviews the relevant literature on each research topic,thus providing an overview and summary of the current status and characteristics of LIS research in China,as well as highlighting the research gaps and future prospects.