| Currently,big data technology has been studied and applied to varying degrees in various fields in China,playing an important role in solving key bottleneck problems in related application fields.How to use scientific and effective methods to gain insights into the development of disciplines in the field of big data technology and explore the evolution of research topics in this field has become very important.In this context,this article adopts bibliometric and thematic modeling methods to study the current development status and thematic distribution of big data technology,aiming to clarify the development context of big data technology from the perspective of literature information development and provide some reference for relevant researchers.In the process of carrying out the research work in this article,following the principle of problem orientation,following the idea of "proposing problems,analyzing problems,and solving problems",using bibliometric visualization software and Python programming language tools,some achievements have been made in the distribution of literature disciplines,analysis of disciplinary development trends,and distribution of thematic literature.The main details include:(1)Sort out and analyze the normative structure of literature indexing,including the core metadata of literature description,topic annotation of literature,and journal evaluation methods.Based on this,construct the analytical framework of this article,laying the foundation for conducting research on literature distribution patterns and topic distribution analysis in the field of bibliometrics;(2)Analyze and predict the distribution patterns and development trends of literature related to big data technology.We used literature information retrieval technology to investigate 3165 articles included in the CNKI database from 2003 to2022.We used bibliometric correlation analysis methods and analyzed the distribution of the surveyed 3165 articles based on core metadata elements such as discipline,theme,journal sources,and citations,and summarized the development patterns of the literature;(3)Research and analyze the theme and hot topic distribution of literature related to big data technology.Firstly,based on bibliometric research,LDA topic modeling method is used to analyze and mine topic words;Secondly,using probability as a basic tool,research on literature word topic and topic distribution will be conducted for the selected 5 topic words;Finally,an empirical analysis was conducted on the research content using Python as a technical tool.The research findings of this article are: firstly,the current research on big data technology in China mainly focuses on disciplines such as computer science,administrative management,education,and economics;Second,the literature distribution is relatively centralized,and the high-quality literature in the survey sample is basically distributed in 30 types of journals in the core area;Thirdly,the theme mainly covers five core areas: university education and teaching,data analysis methods,information privacy protection,information services,and core technologies.Among them,information services and core technologies are two research topics with a focus on bias.The visualization and analysis of these research conclusions can provide some reference and reference for the development of the discipline field.The research findings of this paper are as follows: First,the current domestic research on big data technology mainly focuses on computer,administrative management,education and economics;Second,there are different levels of documents and periodicals,and the high-quality documents in the survey sample are basically distributed in 30 types of periodicals in the core area;Third,the theme mainly covers five core key areas,including university education,data analysis,privacy protection,smart governance,and information services.Among them,smart governance and information services are two key research topics.The visual presentation and analysis of these research conclusions can provide some reference for the development of the discipline. |
