Hierarchical Clustering and Regression Classification based Review analysis on Movie based Applications

Abstract

In recent year sentiment analysis plays an important role in the opinion mining where the research on the analysis is mainly focused on the extraction of opinions and their emotions towards a particular application in the web. This paper presents review analysis of movie from various movie based applications. This paper concentrates more on the fundamental aspects of sentimental analysis which includes different methods of analyzing the reviews including data extraction, clustering and classification. In this paper extraction of the reviews from various movie based applications like IMDB, Pay tm etc.,, can be taken and formed the Movie dataset, This Movie API consists of movie name, comments, reviews, rating, emoji’s etc., In this paper first data pre-processing techniques is applied to clean the dataset and then apply the hierarchical clustering for the attributes taken and then regression based classification on the attributes to form a cluster based on negative and the positive reviews provided by the different users and finally determining the accuracy using proposed hierarchical clustering and regression technique with existing decision tree technique and the accuracy of proposed technique more accuracy is achieved.