Business reviews classification using sentiment analysis

被引:22
作者
Salinca, Andreea [1 ]
机构
[1] Univ Bucharest, Fac Math & Comp Sci, Bucharest, Romania
来源
2015 17TH INTERNATIONAL SYMPOSIUM ON SYMBOLIC AND NUMERIC ALGORITHMS FOR SCIENTIFIC COMPUTING (SYNASC) | 2016年
关键词
sentiment analysis; opinion mining; classification; text reviews;
D O I
10.1109/SYNASC.2015.46
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
the research area of sentiment analysis, opinion mining, sentiment mining and sentiment extraction has gained popularity in the last years. Online reviews are becoming very important criteria in measuring the quality of a business. This paper presents a sentiment analysis approach to business reviews classification using a large reviews dataset provided by Yelp: Yelp Challenge dataset. In this work, we propose several approaches for automatic sentiment classification, using two feature extraction methods and four machine learning models. It is illustrated a comparative study on the effectiveness of the ensemble methods for reviews sentiment classification.
引用
收藏
页码:247 / 250
页数:4
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