Sentiment Analysis and Prediction using Text Mining

作者:Lakshmi, K. Prasanna; Shraddha, V.; Abhinava, V.; Kavya, K.; Gayathri, R. 刊名:Indian Journal of Science and Technology 上传者:刘庆春

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*Author for correspondence Indian Journal of Science and Technology, Vol 10(28), DOI: 10.17485/ijst/2017/v10i28/113441, July 2017 ISSN (Print) : 0974-6846 ISSN (Online) : 0974-5645 Sentiment Analysis and Prediction using Text Mining K. Prasanna Lakshmi, V. Shraddha, V. Abhinava, K. Kavya and R. Gayathri Department of Information and Technology, GRIET, Hyderabad - 500090, Telangana, India; prasannakompalli@gmail.com, shraddhavasi@gmail.com, abhinavavoruganti@gmail.com, kavyakonda95@gmail.com, rangagayatri@gmail.com Keywords: Cosine Similarity, Prediction, Reviews, Sentiment Score, User Sentiment Abstract Objectives: The main aim of the proposed system is to predict the ratings of a textual review using the concept of sentiment analysis. Prediction is an important process to know about the user sentiment. Methods/Statistical Analysis: This work has a sentiment-based rating prediction method (RPS) to upgrade the prediction accuracy in any recommender system. It basically constitutes of a factor used in predicting the rating. Initially, we calculate user’s sentiment on an item/ product based on user sentimental approach. We apply cosine similarity to find user’s sentiment similarity between the users. By taking user’s sentiment similarity into consideration we can fill the missing values and predict the rating for the products that have not been reviewed by the users. Findings: We assess the above two sentimental factors on a sample dataset collected. Eventually the results show

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