基于语义块的事件倾向性分析研究  

Event Sentiment Analysis Based on Semantic Chunks

作　　者：韦向峰[1] 张全[1] 缪建明[1] 池毓焕[1] 

机构地区：[1]中国科学院声学研究所,北京100190

出　　处：《中文信息学报》2012年第3期44-48,共5页Journal of Chinese Information Processing

基　　金：国家语委"十二五"科研项目(YB125-53);中国科学院学部咨询项目(Y129091211)

摘　　要：事件的倾向性分析对网络舆情分析和事件趋势分析都具有重要意义。该文把影响倾向性分析的词语分为四类:对象词、褒贬词、逻辑词和程度词,建立了语句倾向性分析的二元模型和三元模型,在语句语义块分析的基础上实现对语句和篇章的倾向性获取。实验中首先确定三个事件实例的关键对象和立场,然后根据语句倾向性分析获得文章对于对象的褒贬态度和立场。实验表明语义块的范围限制有助于提高事件倾向性分析的准确性,立场分析则是事件倾向性分析的关键所在。The event sentiment analysis is of substantial significance in mining the public opinion and hot topics.The words which impact the effect of event sentiment analysisare classified into four categories： object,polarity,logic and grade words.This paper proposes the bi-gram and tri-gram models forathe sentence sentiment analysis,and the opinion of an article can thus be achieved via the semantic chunk.In the experiment,the key objects and their opinions are confirmed by human,then the system can obtain the opinion of an article based on the sentence sentiment analysis results.Experimental results show that semantic chunks improve the accuracy of analysis and standpoint decision is a key step in in the event sentiment analysis.

关 键 词：倾向性 语义块 立场分析 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]