DocumentCode :
3757966
Title :
Business Reviews Classification Using Sentiment Analysis
Author :
Andreea Salinca
Author_Institution :
Fac. of Math. &
fYear :
2015
Firstpage :
247
Lastpage :
250
Abstract :
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.
Keywords :
"Feature extraction","Business","Sentiment analysis","Classification algorithms","Support vector machines","Training","Algorithm design and analysis"
Publisher :
ieee
Conference_Titel :
Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), 2015 17th International Symposium on
Type :
conf
DOI :
10.1109/SYNASC.2015.46
Filename :
7426090
Link To Document :
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