基于语料库话语分析的科学知识图谱分析
Analysis of the Scientific Knowledge Graph of Corpus-Based Discourse Analysis

DOI: 10.12677/ML.2019.73050, PP. 363-383

Keywords: 话语分析，语料库，CiteSpace，知识图谱
话语分析，语料库，CiteSpace，知识图谱

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Abstract:

本文借助CiteSpace文献计量工具，以Web of Science数据库1988~2018年(3月)收录数据为来源，绘制基于语料库的话语分析近28年来的科学知识图谱。利用CiteSpace软件，我们绘制了基于语料库的话语分析领域的文献共被引图谱，根据图谱的聚类结果，对9个较大的文献聚类进行了深入分析，涵盖了基于语料库的话语分析的主要方向。此外，我们还对知识图谱中具有高被引、高中介中心性和高突变性的关键节点文献进行了分析，梳理了基于语料库的话语分析各个方向的重要文献，并结合图谱的时间线功能分析了潜在的研究热点。
Scientific knowledge graphs which cover the literature of corpus-based discourse analysis in the past 28 years were generated in this paper with the help of a bibliometric tool, a piece of software named CiteSpace, and with the source data (1988~2018 (March)) from Web of Science database. The major knowledge graph employed in this paper is the co-citation graph of corpus-based discourse analysis generated by CiteSapce. According to this graph, we found 9 major literature clusters covering the main research aspects in the field of corpus-based discourse analysis and we have analyzed these 9 clusters in detail. Important articles or books in each cluster were analyzed in this process. Furthermore, we also analyzed those key points in the graph, which had high citation frequency, high centrality value, or high citation burstness value. Last but not least, we tried to explore potential research hotspot by using the timeline function of CiteSpace.

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