随着民族地区信息化建设的不断推进,中国少数民族语言网络舆情研究也逐渐引起了大家的关注,文本分类和情感分析模块是舆情系统的重要组成部分。传统的文本分类方法主要通过统计字面上的词语重复次数,而对于文字背后的语义关联考虑甚少。该文重点介绍了一种基于LDA模型在少数民族语言(以彝文为例)网络舆情信息情感分析方面的应用,对文字隐含的主题进行建模,通过挖掘少数民族网页上的舆情信息所蕴含的主题,以及对这些主题进行情感分析,在事件全面爆发之前,采取应急措施。
With the development of ethnic areas of information technology, the Chinese minority language network public opinion research has gradually attracted everyone's attention, text classification and sentiment analysis module is an important part of public opinion of the system. Traditional text classification methods, mainly through word repetitions statistics literally, and semantic association little consideration for the text behind. This article focuses on the LDA model based on minority languages (with Yi for example) the application of information network public opinion sentiment analysis aspects of the theme of the text implied modeling, data mining minorities through public opinion on a web page that contains the theme, as well as sentiment analysis of these topics, before the incident broke out, Bian take emergency measures.