基于情感本体的主题网络舆情倾向性分析

Tendency Analysis of Thematic Networks Public Opinion Based on Sentiment Ontology

  • 摘要: 在研究文本倾向性识别方法的基础上,分别实现基于文本分类、基于语义规则模式和基于情感词的倾向性分析算法.研究情感本体构建和基于HowNet与主题领域语料的情感概念选择方法,两者结合能提高情感本体中概念的全面性和领域针对性.利用情感本体抽取特征词并判断其情感倾向度,结合句法规则及程度副词影响,用特征情感倾向度作为特征权重,采用机器学习的方法对主题网络舆情web文本进行倾向性分析.实验表明,其分析结果有更高的准确率和召回率,实现方案的普遍性和稳定性值得进一步研究.

     

    Abstract: The algorithms of tendency analysis based on text classification, semantic rules pattern and sentiment word are designed based on the study of the text tendency recognition method. The combination of the sentiment ontology construction and the emotional concept selection method based on HowNet and subject areas corpus can improve the concept comprehensiveness and domain pertinency of sentiment ontology. The keywords are extracted and their degrees of emotional tendencies are determined by sentiment Ontology. The degree of emotional tendencies is used as the characteristic weight combining the syntactic rules and the adverbs of the sentiment. The emotional analysis of web texts for thematic networks public opinion is done by machine learning methods. The experiments show that the analysis results has higher precision and recall. The universality and stability of its implementation deserves is worth of further study.

     

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