Theoretical study of sentiment analysis using support vector machine

This work involves the study of Sentiment Analysis with the help of Support Vector Machine. The goal of this study is to understand processes involved in machine learning for sentiment analysis of any given data set. Based on the content of any given text, we are looking to classify the set of words as being positive or negative which defines the text’s overall sentiment, opinion, or appraisal about an element or facet of the element from an opinion holder. By studying features to categorize the content of a given text, we learn supervised learning techniques provided by support vector machines.