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基于句法与主题扩展的中文微博情感倾向性分析模型
引用本文:陆浩,牛振东,张楠,孙星恺,刘文礼.基于句法与主题扩展的中文微博情感倾向性分析模型[J].北京理工大学学报,2014,34(8):824-830.
作者姓名:陆浩  牛振东  张楠  孙星恺  刘文礼
作者单位:北京理工大学计算机学院,北京 100081;中国科学院自动化研究所复杂系统管理与控制国家重点实验室,北京100190;北京理工大学计算机学院,北京 100081;中国自动化学会,北京100190;中国科学院自动化研究所复杂系统管理与控制国家重点实验室,北京100190;国防科学技术大学军事计算实验与平行系统研究中心,湖南,长沙410073
基金项目:国家自然科学基金资助项目(61250010);中国科学院规划与决策科技支持系统建设资助项目(2F11N06)
摘    要:微博数据具有微博文本长度不一,文本内容主题发散性,夹杂微博专用符号等特性,需要一种融合句法分析、领域知识、表情符号等多因素的综合建模方法对社会、娱乐、安全等多领域微博进行情感分析. 文章提出了一种面向主题的中文微博情感建模方法,该模型涵盖了数据预处理、句法分析、主题扩展、领域知识、情感词上下文极性调整、表情符号等内容,最后以新浪微博采集数据,选取3个领域主题进行了实验,在特定的实验环境下,得到了较高的分析准确率. 

关 键 词:微博  情感分析  句法分析  主题扩展
收稿时间:6/8/2013 12:00:00 AM

A Model for Sentiment Classification of Chinese Microblog Based on Parsing and Theme Extension
LU Hao,NIU Zhen-dong,ZHANG Nan,SUN Xing-kai and LIU Wen-li.A Model for Sentiment Classification of Chinese Microblog Based on Parsing and Theme Extension[J].Journal of Beijing Institute of Technology(Natural Science Edition),2014,34(8):824-830.
Authors:LU Hao  NIU Zhen-dong  ZHANG Nan  SUN Xing-kai and LIU Wen-li
Institution:School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China;The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China;School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China;Chinese Association of Automation, Beijing 100190, China;The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China;Research Center on Computational Experiments and Parallel Systems, National University of Defense Technology, Changsha, Hu'nan 410073, China
Abstract:The main features of microblog include different lengths, divergence of its themes, and inclusion of special symbols. It's essential for building a comprehensive modeling method, which integrating dependency sentence analysis, domain knowledge and emotions to analyze sentiment of microblog in various aspects, such as society, entertainment, security. In this paper, a topic-oriented sentiment analysis model for Chinese microblog was proposed, this model covers data preprocessing, dependency sentence analysis, theme extension, domain knowledge and rules, dynamic adjustment of polarity of sentiment words and emotions. Through the experiments of Sina weibo data from three different domains, this method obtains high analytical accuracy under specific experimental environment.
Keywords:microblog  sentiment analysis  syntactic analysis  theme extension
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