Analysis of different approaches to Sentence-Level Sentiment Classification
Vandana S. Jagtap, Karishma Pawar · 2013
Abstract: Sentiment classification is a way to analyze the subjective information in the text and then mine the opinion. Sentiment analysis is the procedure by which information is extracted from the opinions, appraisals and emotions of people in regards to entities, events and their attributes. In decision making, the opinions of others have a significant effect on customers ease, making choices with regards to online shopping, choosing events, products, entities. The approaches of text sentiment analysis typically work at a particular level like phrase, sentence or document level. This paper aims at analyzing a solution for the sentiment classification at a fine-grained level, namely the sentence level in which polarity of the sentence can be given by three categories as positive, negative and neutral. whereas sentiment analysis attempts to divide the language units into three categories; negative, positive and neutral. With the passage of time and a need for better understanding and extraction, momentum slowly increased towards sentiment classification and semantic orientation. In this paper, various methods proposed for sentence-level sentiment classification have been analyzed. 2. Sentiment Classification Sentiment classification is a new field of Natural Language Processing that classifies subjectivity text into positive or negative.