考虑语境的微博短文本挖掘:情感分析的方法  

Microblog Short Text Mining Considering Context:A Method of Sentiment Analysis

作　　者：史伟 付月 SHI Wei;FU Yue(School of Economics and Management,Huzhou University,Huzhou,Zhejiang 313000,China;Qiuzhen College,Huzhou University,Huzhou,Zhejiang 313000,China)

机构地区：[1]湖州师范学院经济管理学院,浙江湖州313000 [2]湖州师范学院求真学院,浙江湖州313000

出　　处：《计算机科学》2021年第S01期158-164,共7页Computer Science

基　　金：国家社会科学基金一般项目“重大突发事件中网民情感状态演变规律及引导研究”的阶段性成果(20BXW013)。

摘　　要：传统基于词典的情感分析方法中情感词语的极性和强度是固定和静态的,没有考虑情感词语随不同语义环境极性和强度的变化。为此,提出一种考虑语境的基于情感本体和情感圈的微博短文本情感分析方法。采用情感圈方法考虑不同语境中词语的共现模式,以捕获它们的语义并更新情感词语的极性和强度。结合已构建的情感本体和语义量化规则,建立考虑语义环境的微博短文本挖掘方法。实验结果表明,该方法从实体级和微博级两个层面,在精度、召回率、F值和准确率几个指标上都明显优于基线方法。In the traditional dictionary based sentiment analysis,the polarity and intensity of sentiment words are fixed and static,without considering the change of polarity and intensity of sentiment words with different semantic environments.This paper proposes a sentiment analysis method of microblog short text based on sentiment ontology and sentiment circle considering context semantics.In order to capture their semantics and update the polarity and intensity of emotional words,we use the sentiment circle method to consider the co-occurrence patterns of words in different contexts.Combined with the constructed emotion ontology and semantic quantitative rules,a method of microblog short text mining considering semantic environment is established.The experimental results show that the proposed method is superior to the baseline method in terms of accuracy,recall,F value and accuracy from both entity level and microblog level.

关 键 词：微博短文本 情感本体 情感圈 情感分析 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术]