SSCI图书馆学与情报学领域作者主题可视化分析
Visual Analysis of Author-topic of Library and Information Science in SSCI
孙奇1
作者信息
- 1. 新疆财经大学图书馆 新疆乌鲁木齐 830012
- 折叠
摘要
[目的/意义]旨在发现当前国际上LIS研究领域中的结构化特征,为未来相关学术研究和行业发展提供借鉴.[方法/过程]对 2009-2022 年SSCI中LIS分类下的文献题录数据建立作者—主题模型并进行可视化解读.在此基础上依据论文引证网络,将重点被引作者主题分布与领域整体主题分布作对比分析.[结果/结论]LIS相关研究与医学信息学、社会信息学相互交叉并拓展出了数据驱动型研究簇,其中企业发展等相关研究受到了领域内学者的广泛关注.
Abstract
[Purpose/significance]The aim is to discover the structural characteristics in the current international LIS research field and provide reference for the future academic research and industry development.[Method/process]This paper eatablishes an author-topic model for bibliographies under LIS classification in SSCI from 2009 to 2022 and carries on visual interpretation.On this ba-sis,the topic distribution of key cited authors is compared with the overall topic distribution in the field according to the paper citation network.[Result/conclusion]LIS related research intersects with medical informatics and social informatics and expands data-driven research cluster,in which enterprise development and other related research have attracted extensive attention from scholars in the field.
关键词
作者—主题模型/作者—主题社区/二分网络/可视化分析Key words
author-topic model/author-topic community/binary network/visual analysis引用本文复制引用
出版年
2024
NETL
NSTL
万方数据