Textual Reviews based on Sentimental Analysis
Sentiment analysis is an application of natural language processing. We are focusing on textual analysis. This is a very popular field of research in text mining. It is also known as emotion extraction or opinion mining. We basically comb user opinions to convert into measured rating system for better understanding of the response given by the user. Any type of business works on the basis of response to the product without which there is no type of progress whatsoever. The basic idea is to find the polarity of the text and classify it into positive, negative or neutral. It helps in review decision making. To perform sentiment analysis, one has to perform various tasks like subjectivity detection, sentiment classification, aspect term extraction, feature extraction etc. This paper presents the survey of main approaches used for sentiment classification. We fuse three factors— user sentiment similarity, interpersonal sentimental influence, and item’s reputation similarity—into our recommender system to make an accurate rating prediction.