Microblog Sentiment Classification Based on Supervised and Unsupervised Combination

被引：0
|
作者：
Pei, Shaojie [1 ]
Zhang, Lumin [1 ]
Li, Aiping [1 ]
Liu, Yusha [2 ]
机构：
[1] Natl Univ Def Technol, Sch Comp, Changsha, Hunan, Peoples R China
[2] Zhejiang Univ, Dept Opt Engn, Hangzhou, Peoples R China
来源：
TRUSTWORTHY COMPUTING AND SERVICES | 2014年 / 426卷
关键词：
Sentiment classification; Naive Bayes; Semantic similarity; Microblog;
D O I：
10.1007/978-3-662-43908-1_18
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Millions of users are sharing their views and opinions in microblog everyday, which makes sentiment classification in microblog be an important and practical issue in social networks. In this paper, we combined the conversional supervised algorithm with unsupervised methods to conduct sentiment analysis. Specifically, we divided the content into two parts: those with emoticons and those without emoticons, and use multiple optimization for the two different parts. Practical evaluation shows that our methods could perform effectively and efficiently for this attracting problem.
引用
收藏
页码：138 / 145
页数：8
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