DocumentCode :
266877
Title :
Numeric rating of Apps on Google Play Store by sentiment analysis on user reviews
Author :
Islam, Md Rafiqul
Author_Institution :
Dept. of Comput. Sci., American Int. Univ. - Bangladesh, Dhaka, Bangladesh
fYear :
2014
fDate :
10-12 April 2014
Firstpage :
1
Lastpage :
4
Abstract :
The sudden eruption of sentiment analysis and opinion mining has opened new possibilities to improve our information gathering interests. We are always keen to know what others say about the devices or applications we are going to use. Its observed that sometimes the numeric rating has vast difference than the reviews given by the users. To remove this ambiguity a unified rating system has been proposed here. The starred rating and a generated numeric polarity of the reviews are combined to generate the final rating. The proposition is based on sentiment analysis and an optimized probabilistic approach described by a group of researchers. The approach is proved for its efficiency in a diverse corpus of writings where the targets are of different categories.
Keywords :
Internet; data mining; Apps; Google Play Store; diverse corpus; numeric rating; opinion mining; optimized probabilistic; sentiment analysis; starred rating; unified rating system; user reviews; Feature extraction; Google; Knowledge discovery; Probabilistic logic; Sentiment analysis; Writing; Apps Review; Numeric Rating; Polarity Extraction; Sentiment Analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical Engineering and Information & Communication Technology (ICEEICT), 2014 International Conference on
Conference_Location :
Dhaka
Print_ISBN :
978-1-4799-4820-8
Type :
conf
DOI :
10.1109/ICEEICT.2014.6919058
Filename :
6919058
Link To Document :
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