摘要
【目的】梳理近年来引用内容分析研究进展,理清研究方向及技术发展趋势。【文献范围】利用知网、Scopus、语义学者等搜索平台,以“引文全文本”、“引文上下文”、“引文内容”、“引用内容”、“citation content”等关键词进行检索,并进行人工筛选。【方法】从相关概念辨析、主要研究方向、关键技术、分析工具和平台4个方面对引用内容分析相关研究进行归纳和对比分析,提出现存问题和未来研究方向。【结果】引用内容分析在引用动机、引用评价、知识流向、论文推荐等研究方向出现一些新的研究思路和方法;在引用内容分析关键共性技术方面,引用句抽取、引用位置识别、引用情感分析、引用知识点识别等方面均取得进展。【局限】主要从宏观层面归纳总结引用内容分析相关研究,未进行各个方面内容的深入阐述。【结论】引用内容分析相对于引文分析具有独特的优势,随着自然语言处理技术的快速迭代,其发展前景广阔。
[Objective]This paper reviews the research progress of citation content analysis in recent years and clarifies the research direction and technology development trend.[Coverage]HowNet,Scopus,Semantic Scholar,and other search platforms are used to search papers with keywords such as“citation full text”,“citation context”,“citation content”and so on,and manual screening is conducted.[Methods]Research on citation analysis is summarized and compared from four aspects:discrimination of relevant concepts,main research directions,key technologies,analysis tools and platforms,and existing problems and future research directions are raised.[Results]New ideas and methods are emerging in citation content analysis research directions such as citation motivation,citation evaluation,knowledge flow,and paper recommendation.Key common technologies for citation content analysis have achieved much progress in citation extraction,citation location identification,citation sentiment analysis,and knowledge point identification.[Limitations]It mainly summarizes and analyzes the relevant research from the macro level and does not elaborate on the content in all aspects in-depth.[Conclusions]Citation content analysis has unique advantages over citation analysis.With the rapid iteration of natural language processing technology,it will have a broad development prospect.
作者
王露
乐小虬
Wang Lu;Le Xiaoqiu(National Science Library,Chinese Academy of Sciences,Beijing 100190,China;Department of Library,Information and Archives Management,School of Economics and Management,University of Chinese Academy of Sciences,Beijing 100190,China)
出处
《数据分析与知识发现》
CSSCI
CSCD
北大核心
2022年第4期1-15,共15页
Data Analysis and Knowledge Discovery
关键词
引用内容
引用内容分析
机器学习
深度学习
Citation Context
Citation Context Analysis
Machine Learning
Deep Learning
