期刊文献+

基于多种情感特征的网络文本倾向性判别方法研究 被引量:1

Research on the Method of Network Text Orientation Discrimination Based on Multiple Sentiment Features
下载PDF
导出
摘要 网络文本的情感倾向性分析对于电子商务、网络信息安全、网络舆情等方面具有非常重要的意义。本文在对文本倾向性分析的常用方法作了分析和研究的基础上,提出了一种综合情感词语、否定词、程度副词、关联词和词句类型等多种特征计算词句的极性值,进而判别文本情感倾向性的方法。实验结果表明,与ku提出的算法相比,该方法更能有效地判定文本情感倾向性。 The analysis of the sentiment orientation of the network text is very important for the electronic commerce, the network information security, the network public opinion and so on. In this paper, the general method of text orientation analysis is studied. We propose a new method to calculate the polarity value of the words and to judge the sentiment orientation of text, which comprehensives a variety of characteristics, such as the emotional words, negative words, adverbs of degree, related words, and so on. The experimental results show that the proposed method is more effective than the Ku algorithm for judging sentiment orientation.
作者 樊康新 FAN Kang-xin (School of Computer Science and Technology, Nantong University, Nantong 226019, China)
出处 《电脑知识与技术》 2015年第8期18-21,共4页 Computer Knowledge and Technology
基金 南通大学自然科学基金资助项目(11Z075)
关键词 情感词典 情感特征 网络文本 文本倾向性 倾向性分析 sentiment lexicon sentiment feature network text text orientation orientation analysis
  • 相关文献

参考文献7

  • 1Pang B,Lee L, Vaithyanathan S. Thumbs up? Sentiment clas- sification using machine learning techniques[C]. Proceedingsof the Conference on Empirical Methods in Natural Language Processing(EMNLP).USA Philadelphia:2002:79-86.
  • 2李素科,蒋严冰.基于情感特征聚类的半监督情感分类[J].计算机研究与发展,2013,50(12):2570-2577. 被引量:23
  • 3徐琳宏,林鸿飞,杨志豪.基于语义理解的文本倾向性识别机制[J].中文信息学报,2007,21(1):96-100. 被引量:123
  • 4Ku Lun-Wei, Liang Yu-Ting, Chen Hsin-His. Opinion ex- traction,summarization and tracking in news and blog corpora [C]//Proceedings of the 2006 AAAI Symposium on Computa- tional Approaches to Analyzing Weblogs. Menlo Park: AAAI Press, 2006:100-107.
  • 5董振东,董强..HowNet[EB/OL]..http://www.keenage.com/,,[2008-01-13]..
  • 6刘群,李素建.基于《知网》的词汇语义相似度计算[J].计算机语言学与中文信息处理,2007.31(7):59-76.
  • 7朱嫣岚,闵锦,周雅倩,黄萱菁,吴立德.基于HowNet的词汇语义倾向计算[J].中文信息学报,2006,20(1):14-20. 被引量:327

二级参考文献37

  • 1董振东.语义关系的表达和知识系统的建造[J].语言文字应用,1998(3):79-85. 被引量:59
  • 2金珠,林鸿飞,赵晶.基于HowNet的话题跟踪及倾向性分类研究[J].情报学报,2005,24(5):555-561. 被引量:21
  • 3朱嫣岚,闵锦,周雅倩,黄萱菁,吴立德.基于HowNet的词汇语义倾向计算[J].中文信息学报,2006,20(1):14-20. 被引量:327
  • 4董振东 董强.[EB/OL].知网.http://www.keenage.com,.
  • 5Vasileios Hatzivassiloglou, Kathleen R. McKeown. Predicting the semantic orientation of adjectives[A]. In: Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and the 8th Conference of the European Chapter of the ACL[C], 1997:174- 181.
  • 6Turney, Peter, Littman Michael. Measuring praise and criticism: Inference of semantic orientation from association[J]. ACM Transactions on Information Systems, 2003, 21(4): 315- 346.
  • 7Turney ,Peter. Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews[A]. In: Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics[C]. 2002:417 -424.
  • 8Bo Pang,Lillian Lee, Shivanathan Vaithyanathan. Thumbs up? Sentiment classification using machine learning techniques[A]. In Proceedings of the 2002 Conference on Empirical Methods in Natural Language Processing[C]. 2002:79 - 86.
  • 9Bo Pang,Lillian Lee. Seeing Stars: Exploiting Class Relationships for Sentiment Categorizalion with respect to Rating Seales[A]. ACL2005, 115-124.
  • 10K Dave, S lawrence, DM Pennock. , Mining the peanut gallery: opinion extraction and semantic classification of product reviews[A]. WWW2003, 519-28.

共引文献433

同被引文献9

引证文献1

二级引证文献6

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部