计算机应用与软件2016，Vol.33Issue(8)：43-49,7.DOI:10.3969/j.issn.1000-386x.2016.08.010
基于领域文法的微博舆情分析方法及其应用
A METHOD FOR ANALYSING PUBLIC OPINIONS IN MICROBLOGS BASED ON DOMAIN-SPECIFIC GRAMMAR AND ITS APPLICATION
摘要
Abstract
Traditional public opinion analysis method has two defects:since lacking necessary semantic processing on public opinion texts, traditional network public opinions analysis method based on keywords or bag-of-words usually has inaccurate analysis results,i.e.,the false negative and false positive rates are relatively high;and because of sparse data,generally the method can’t timely catch the ″signs″of public opinions in early stage of public opinion development.To solve these problems,this paper presents a domain-specific grammar-based analysis method for analysing microblogging grammars,and puts forward a list of universal design principles and an analysis method for domain-specific grammar.Compared with statistical method,the advantages and the innovation points of domain-specific grammar-based method include:the domain-specific grammar can still work well in the case of data sparsity;the work mode of domain-specific grammar does not need to make statistics on information,and will not be affected by the distance of words.The domain-specific grammar-based method can well extract really useful information but will not be affected by the word collocation as the statistical method is.To demonstrate the utility of our method,we choose the public opinions of anti-corruption as the verification application.Experiments show that the grammar of public opinions in regard to corruption domain can well recognise and extract the text contents of microblogging public opinions of corruption category,therefore reaches the goal of corruption public opinions inspection.关键词
微博舆情分析/领域文法/文法设计/反贪腐领域Key words
Microblogging public opinion analysis/Domain-specific grammar/Grammar design/Anti-corruption domain分类
信息技术与安全科学引用本文复制引用
张露晨,张良,孙昊良,方芳,曹阳,曹存根..基于领域文法的微博舆情分析方法及其应用[J].计算机应用与软件,2016,33(8):43-49,7.基金项目
国家自然科学基金项目（91224006，61035004，61173063，61203284）；科技部项目（201303107）。 （）
