Mining Online Reviews in Websites for Predicting Sales Performance

• Divagar S
• Joesph Raymond V

OnlineReview mining, hidden sentiment analysis, prediction, S-PLSA, ARSA

Nowadays people posting reviews are increasing and it gives us the knowledge to buy the products. People can express their sentiments through reviews posted in websites. By these reviews we can predict the movie sales performance. The question is how the sentiment factor can be analyzed in the reviews? Reviews are analyzed by Sentiment PLSA which helps us to find the unknown factors in the reviews and helps us to classify the reviews. Then we have to predict the sales performance, for the prediction regression is suitable way to do and we suggest an autoregressive sentiment (ARSA) Aware Model. To improve the prediction accuracy to enhance the best quality factor we also consider an autoregressive sentiment and quality aware model (ASQA)to build the quality for mining reviews sales performance in movie domain.

Published

 Vol. 2 Issue. 1 Pages. 1184-1186

Divagar S, Joesph Raymond V. "Mining Online Reviews in Websites for Predicting Sales Performance".INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH ISSN:2321-9939, Vol.2, Issue 1, pp.1184-1186, URL :https://rjwave.org/ijedr/papers/IJEDR1401211.pdf

Volume 2 Issue 1 

Pages. 1184-1186

Published Paper PDF : https://rjwave.org/ijedr/papers/IJEDR1401211.pdf

Published Paper URL : https://openrgate.org/viewfulldetails.php?id=542

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition