北京大学学报(自然科学版)

基于社会关系网络的半监督情感分类

薛云霞,李寿山,王中卿   

  1. 苏州大学自然语言处理实验室, 苏州 215006;
  • 收稿日期:2013-06-17 出版日期:2014-01-20 发布日期:2014-01-20

Semi-supervised Sentiment Classification with Social Network

XUE Yunxia, LI Shoushan, WANG Zhongqing   

  1. Natural Language Processing Lab, Soochow University, Suzhou 215006;
  • Received:2013-06-17 Online:2014-01-20 Published:2014-01-20

摘要: 基于样本的社会关系, 提出一种新的半监督学习方法, 创建一种基于文档?词及社会关系的二部图模型, 并根据标签传播算法将未标注样本加入到分类器的构建中。实验结果表明, 加入社会关系网络的半监督情感分类方法明显优于传统的仅利用评论文本信息的半监督情感分类方法。

关键词: 情感分类, 半监督, 社会关系网络, 标签传播, 自然语言处理

Abstract: Based on the social connection anong the comments in the social network, the authors propose a new approach of semi-supervised sentiment classification, and provide a document-word and social connection bipartite graph structure and apply to label propagation algorithm. Evaluation shows that the proposed approach performs better than that which only considers comment textual information.

Key words: natural language processing, sentiment classification, semi-supervised, social network, label propagation

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