计算机科学 ›› 2021, Vol. 48 ›› Issue (11A): 17-21.doi: 10.11896/jsjkx.210300172

• 智能计算 • 上一篇    下一篇

基于CiteSpace的中文评论文本研究现状与趋势分析

李建兰, 潘岳, 李小聪, 刘子维, 王天宇   

  1. 合肥工业大学管理学院 合肥230009
  • 出版日期:2021-11-10 发布日期:2021-11-12
  • 通讯作者: 李建兰(1577251726@qq.com)
  • 基金资助:
    合肥工业大学省级大学生创新项目(S202010359165)

Chinese Commentary Text Research Status and Trend Analysis Based on CiteSpace

LI Jian-lan, PAN Yue, LI Xiao-cong, LIU Zi-wei, WANG Tian-yu   

  1. School of Management,Hefei University of Technology,Hefei 230009,China
  • Online:2021-11-10 Published:2021-11-12
  • About author:LI Jian-lan,born in 2000,undergra-duate.Her main research interests include electronic commerce and so on.
  • Supported by:
    Provincial College Student Innovation Project of Hefei University of Technology(S202010359165).

摘要: 自然语言处理一直是人工智能领域中的热点话题,其中基于评论的文本分析吸引了学者的注意。通过对国内关于评论文本分析的文献进行可视化分析,进而掌握该领域的研究现状和前沿发展趋势。以中国知网为数据来源,共选取453篇有效的核心期刊论文,使用CiteSpace软件绘制知识图谱并加以分析。分析结果显示:该领域的文献数量在近15年内整体呈上升趋势;作者之间、研究机构之间的合作关系并不紧密,尚未形成具有凝聚力的研究群体;情感分析、在线评论、深度学习是目前研究的主要热点。从初期的理论基础发展以及应用方向上的扩展,到后期在分析手段和模型上做出改进,学者们对该领域的研究逐渐深入。未来各研究者及研究机构之间的合作关系还需加强,以深度学习为代表的各类模型未来将持续发展和改善。

关键词: CiteSpace, 评论, 情感分析, 特征提取, 文本分析

Abstract: Natural language processing (NLP) has been a hot topic in the field of artificial intelligence (AI) recently,among which commentary-based text analysis has also attracts the attention of scholars.In this study,the research status and frontier development trend can be grasped through a visual analysis of the domestic literature on comment text analysis.A total of 453 valid core journal papers on the field are selected from CNKI as the data source.CiteSpace software is used to draw the knowledge map and analyze it.Analysis results show that the number of literature in this field has been on the rise in past 15 years.The cooperation among authors and among research institutions is not close,and a cohesive research group has not been formed.Sentiment analysis,online comments and deep learning are the main research hotspots at present.From the initial development of theoretical basis and the expansion of application direction,to the improvement of analysis methods and models in the later stage,scholars have gradually deepened the research in this field.In the future,the cooperative relationship between researchers and research institutions needs to be strengthened,and various models which are represented by deep learning will continue to develop and improve in the future.

Key words: CiteSpace, Comment, Feature extraction, Sentiment analysis, Text analysis

中图分类号: 

  • TP391.1
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