Sentiment Detection from Punjabi Text using Support Vector Machine

Abstract

This paper focuses on sentiment analysis on Punjabi News Articles using Support Vector Machine. Sentiment analysis is a field of Natural Language Processing and it is the most trending field of research. Sentiment analysis on Punjabi language is to be performed because of increasing amount of Punjabi content over the web, provides an important aspect for the researchers, organizations, and governments to analyze the user-generated content and get the useful information from it. With the increase in the amount of information being communicated via regional languages like Punjabi, comes a promising opportunity of mining this information. Support Vector Machine approach is used by proposed system to classify the content. Support Vector Machine is a supervised machine learning approach that is be used for classification and regression problems. However, it is mostly used for classification problems. So there is a need to analyze the Punjabi language content and get better understanding of Punjabi text. The work focuses on detecting positive or negative sentiment from Punjabi content. The results of the proposed system depict remarkable accuracy. The accuracy of sentiment analysis on Punjabi news articles using Support vector machine is found to be 90%.