1957-2018年图书情报学论文的可视化分析  

Visualization Analysis of Library and Information Science Papers from 1957 to 2018

作　　者：张毅[1] 李欣[1] ZHANG Yi(Library of East China Normal University,Shanghai 200241,China)

机构地区：[1]华东师范大学

出　　处：《情报科学》2019年第11期169-177,共9页Information Science

基　　金：国家社科基金项目“图书馆异构特藏资源的数字人文研发与共享模式研究”(17BTQ004)

摘　　要：【目的/意义】将人工智能技术与可视化技术相结合,解析文章题名与摘要中包含的隐藏信息,为探索我国图书情报领域的研究历史与现状提供全新研究视角。【方法/过程】从CNKI数据库中下载CSSCI来源期刊中图书情报学领域的全部文章元数据148 956条,利用自然语言处理技术抽取题名与摘要中的标签、分类以及情感倾向,通过统计、聚类、神经网络预测以及知识图谱等方法,绘制期刊下载与被引关系图、构建影响文献被引因素模型、研究热点与情感倾向迁移图以及高质量文章的知识图谱等。【结果/结论】揭示了1957-2018年图书情报领域文献被引与下载的关系,挖掘文献被引的影响因素,找出研究热点的变迁演化以及高被引文献的特征。【Purpose/significance】Integrating artificial intelligence technology with visualization technology, this paper analyzes the hidden information contained in the title and abstract of the article, and provides a new research perspective for exploring the research history and current situation in the field of Library and information in China.【Method/process】Download 148956 metadata of all articles in the field of Library and information science from CNKI database. Use natural language processing technology to extract labels, classifications and emotional tendencies in title and abstract, and drawdownloaded & cited graph of periodicals by means of statistics, clustering, neural network prediction and knowledge map, construct citation factor model, research hotspots and emotional propensity transfer map, and high-quality article knowledge map, etc. [Result/conclusion] This paper reveals the relationship between citation and downloading of documents in the field of Library and information from 1957 to 2018, excavates the influencing factors of citation, and finds out the evolution of research hotspots and the characteristics of highly cited documents.

关 键 词：图书情报学 可视化 知识图谱 自然语言处理 

分 类 号：G250.2[文化科学—图书馆学]