Computer Science ›› 2021, Vol. 48 ›› Issue (6A): 158-164.doi: 10.11896/jsjkx.210200089

• Big Data & Data Science • Previous Articles     Next Articles

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

SHI Wei1, FU Yue2   

  1. 1 School of Economics and Management,Huzhou University,Huzhou,Zhejiang 313000,China
    2 Qiuzhen College,Huzhou University,Huzhou,Zhejiang 313000,China
  • Online:2021-06-10 Published:2021-06-17
  • About author:SHI Wei,born in 1981,Ph.D,professor.His main research interests include business intelligence and affective computing.
  • Supported by:
    General Program of National Social Science Foundation of China “Research on the Evolution Law and Guidance of Netizens' Sentiment State in Major Emergencies”(20BXW013).

Abstract: 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.

Key words: Microblog short text, Sentiment analysis, Sentiment circle, Sentiment ontology

CLC Number: 

  • TP391.1
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