Earticle

초록

영어

Currently, most sentiment analysis of microblog has been focused on coarse-grained sentiment analysis, but fine-grained sentiment is better for reflecting the opinion of the public when they are facing the social focus. Therefore, a hybrid strategy which is a combination of Naïve Bayesian and two-layer CRFs is put forward, which has been applied to the fine-grained sentiment analysis of Chinese microblog. First, microblog is classified into two types: sentiment and non-sentiment by using Naïve Bayesian classification algorithm. And then the first-layer CRFs model is built for the topic emotional sentence. Finally CRFs algorithm is used again to do multi-classification to assign a specific sentiment category. Experimental results show that a good result in sentiment identification based on the combination of Naïve Bayesian and CRFs, and also show the advantage of the combination of Naïve Bayesian and CRFs interrelated with emotional sentence extraction based on CRFs.

목차

Abstract
 1. Introduction
 2. Hybrid Strategy for Fine-Grained Sentiment Analysis
 3. Naïve Bayesian Classifier Design
  3.1. Feature Selection
  3.2. Naïve Bayesian Classification Model Design
 4. Sentiment Analysis based on Conditional Random Fields
  4.1. Conditional Random Fields Model
  4.2. Different Features Definition
  4.3. Model Training
 5. Experimental Results
  5.1. Second-order Headings
  5.2. Results and Observations
 6. Conclusions and Future Work
 Acknowledgements
 References

키워드

저자

• Ouyang Chunping [ School of Computer Science and Technology, University of South China, Hunan Hengyang, 421001, China ]
• Luo Lingyun [ School of Computer Science and Technology, University of South China, Hunan Hengyang, 421001, China ]
• Zhang Shuqing [ School of Computer Science and Technology, University of South China, Hunan Hengyang, 421001, China ]
• Yang Xiaohua [ School of Computer Science and Technology, University of South China, Hunan Hengyang, 421001, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605