Title
Aspect term extraction for sentiment analysis in large movie reviews using Gini Index feature selection method and SVM classifier.
Abstract
With the rapid development of the World Wide Web, electronic word-of-mouth interaction has made consumers active participants. Nowadays, a large number of reviews posted by the consumers on the Web provide valuable information to other consumers. Such information is highly essential for decision making and hence popular among the internet users. This information is very valuable not only for prospective consumers to make decisions but also for businesses in predicting the success and sustainability. In this paper, a Gini Index based feature selection method with Support Vector Machine (SVM) classifier is proposed for sentiment classification for large movie review data set. The results show that our Gini Index method has better classification performance in terms of reduced error rate and accuracy.
Year
DOI
Venue
2017
10.1007/s11280-015-0381-x
World Wide Web
Keywords
Field
DocType
Gini Index,Feature selection,Reviews,Sentiment,Support Vector Machine (SVM)
Data mining,Feature selection,Computer science,Sentiment analysis,Support vector machine,Word error rate,Artificial intelligence,Svm classifier,Classifier (linguistics),Machine learning,The Internet
Journal
Volume
Issue
ISSN
20
2
1386-145X
Citations 
PageRank 
References 
46
1.11
16
Authors
4
Name
Order
Citations
PageRank
asha s manek1471.55
P. Deepa Shenoy211715.23
m chandra mohan3481.89
K. R. Venugopal426748.80