Sentiment Analysis Using Robust Hierarchical Clustering Algorithm for Opinion Mining on Movie Reviews-Based Applications
Mohan Kumar AV1, Nanda Kumar AN2 

1Mohan Kumar AV, Department of Computer Science & Engineering, Visvesvaraya Technological University, Belagavi, India.
2Dr. Nanda Kumar AN, Department of Computer Science & Engineering, GSSS Institute of Engineering and Technology for Women, Mysore, India.
Manuscript received on 02 June 2019 | Revised Manuscript received on 10 June 2019 | Manuscript published on 30 June 2019 | PP: 452-457 | Volume-8 Issue-8, June 2019 | Retrieval Number: H6392068819/19©BEIESP
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Abstract: In recent years, the application of opinion mining for sentiment analysis has gained momentum that concentrates on identification and interpretation of emotions, public opinions regarding a desired subject or object based on textual data. In this paper, sentiment analysis has been performed on movie reviews retrieved from the BookMyShow database available online. The polarity of the review is judged based on the sentiment expression. The fundamental tasks involved in opinion mining including extraction of data, clustering of extracted data as well its classification. The movie reviews are taken from different web pages using BookMyShow application, which provides a Movie API to retrieve the related information like movie name, reviews, rating and other similar content. This paper presents two different techniques for clustering and categorizing. ROCK which clusters and CART to categorize positive and negative words. Criticisms from user comments are also extracted. Ultimately the movie that has the highest percentage of positive reviews from the end users is categorized and total accuracy of user comments is calculated.
Keyword: Classification and Regression Trees [CART] Algorithm, Machine Learning Techniques, Movie API, Robust Hierarchical Clustering Algorithm [ROCK].
Scope of the Article: Music Modelling and Analysis.