Pre-processing Techniques in Sentiment Analysis through FRN: A Review

Abstract

-The objective of the paper is to demonstrate the viability of analyzing online data. It displays a framework which after effects pattern investigation that will be shown as results with various segments introducing positive, negative and neutral. It is challenging task to summarize opinion about the products due to diversity and size. Mining online opinion mining is a difficult text classification task of sentiment analysis. Multivariate content technique called Feature Relation Network that considers semantic data, influencing the syntactic connections between n-gram features. FRN empowers the consideration of heterogeneous n-gram features for improved opinion classification, by joining syntactic data about n-gram relations. FRN selects the features in a more computationally effective way than numerous multivariate and hybrid methods. Appropriate feature selection and representation with sentiment analysis, accuracies using support vector mechanism sentiment analysis; the task of text pre-processing is to be explored.