期刊文献+

基于深度学习的微博情感分析综述 被引量:5

Overview on Sentiment Analysis of Chinese Microblog Based on Deep Learning
下载PDF
导出
摘要 随着21世纪互联网的迅速发展,微博作为一种新型媒体,也成为人们在网络上分享、交流信息和抒发情感的重要工具。随着大数据的分析与研究的热潮,对微博文本信息的舆情监控、商业决策以及情感分析也蕴藏着极大的商业价值。微博情感分析基于微博语料库预处理、微博文本情感特征抽取和微博情感分类三个步骤。本文主要介绍了利用深度学习进行微博情感分析的步骤和方法。 With the rapid development of the Internet in the 21st century, microblog as a new type of media has become an important tool,which people to share, exchange information and express emotions on the Internet.In addition, with the upsurge of big data analysis and research, microblog informations are also contain great commercial value on public opinion monitoring, business decisions and sentiment analysis.The task of microblog emotion analysis is divided into three steps: the pre-processing of microblog corpus, the extraction of emotion feature in microblog text and the classification of emotion in microblog.This paper mainly introduces the classification method of emotion in microblog texts by deep learning.
作者 崔圣杰 李珊珊 孙琦 CUI Sheng-jie;LI Shan-shan;SUN Qi
出处 《信息技术与信息化》 2019年第6期149-151,共3页 Information Technology and Informatization
基金 山东省自然科学基金(ZR2016FM34) 山东省高等学校科研计划(J18KA375) 山东英才学院校级课题(18YCZDXSZR01,18YCYBZR01,19YCSBKT13,19YCSBKT16,19YCXSZZ39,19YCXSZZ40,19YCXSZZ43,19YCXSZC14)
关键词 深度学习 情感分类 微博文本 数据分析 Deep learning Sentiment analysis Microblog text Data analysis
  • 相关文献

参考文献5

二级参考文献29

  • 1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:326
  • 2毛六平,王耀南,孙炜,戴瑜兴.一种递归模糊神经网络自适应控制方法[J].电子学报,2006,34(12):2285-2287. 被引量:9
  • 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:119
  • 4王根,赵军.中文褒贬义词语倾向性的分析[C].第三届学生计算语言学研讨会论集,2006:81-85.
  • 5情感分析用词语集(beta版)[EB/OL].(2007-10-22).http://www.keenage.com.
  • 6PETER D.Turney.Thumbs up or thumbs down? Semantic orientation applied to unsupervised classification of reviews[C]//Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics (ACL)//Philadelphia,PA,USA.2002; 417-424.
  • 7PETER D.Turney and MICHAEL L.Littman.Measuring praise and criticism:inference of semantic orientation from association[J].ACM Transactions on Information Systems,2003,21(4):315-346.
  • 8PETER D.Turney and MICHAEL L.Littman.Unsupervised learning of semantic orientation from a hundred-billion-word corpus[R].Tech.Rep.EGB-1094,National Research Council Canada:2002.
  • 9DAVE K.,LAWRENCE S.,and PENNOCK D..Mining the peanut gallery.,opinion extraction and semantic classification of product reviews[C]//Proceedings of the 22nd International World Wide Web Conference.Budapest,Hungary:2003.
  • 10YUEN Raymond W.M.,CHAN Terence Y.W.,LAI Tom B.Y.et al.Morpheme-based derivation of bipolar semantic orientation of Chinese words[C]//Proc.Of the 20th International Conference on Computational Linguistics (COLING-2004),Geneva,Switzerland.2004:1008-1014.

共引文献93

同被引文献28

引证文献5

二级引证文献11

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