Sentiment Polarity Categorization of Product Reviews using Twitter Data

Abstract

Sentiment analysis, commonly referred to as opinion mining, reveals the attitudes and feelings of consumers about specific goods or services. The sentiment polarity classification, which identifies whether a review is favourable, negative, or neutral, is the fundamental issue with sentiment analysis. There are still some study gaps, as some studies only investigate the positive, neutral, and negative sentiment classes; none of these studies considered more than three classes; also, none of these studies considered the individual and combined effects of the sentiment polarity aspects. No prior method took into account the verb, adverb, adjective, and their combinations, as well as the five sentiment classes and three sentiment polarity traits. This study, provides a method for categorizing online reviews of Instant Videos based on their sentiment. Proposed study makes use of a substantial data set of 500,000 internet reviews. This review-level categorization process Adjective, verb, and two polarity traits are taken into account additionally as well as their pairings with various senses.