Performance Measurement of Multiple Supervised Learning Algorithms for Bengali News Headline Sentiment Classification

Abstract

The reading newspaper is a common habit in today's life. Before reading, news articles all are focused on the news headline. Understanding the meaning of news headlines everybody can easily identify the news types. That means the containing news article provides positive or negative news. Analysis of the sentiment of the news headline is a good solution for this kind of problem. Sentiment Analysis is a chief part of Natural Language Processing. It mines any kinds of opinion and set the sentiment of any text. We proposed a method for Bengali news headline sentiment measurement with different kinds of supervised learning algorithm and their performance. Firstly, we set the sentiment of each news headline then used the classification method to predicting the news headline which was containing a positive or negative headline. After all, Bengali is one of the most used languages in this world. A lot of research work was done previously in a different language but very few in the Bengali language. So, increasing the Bengali language research resource need to develop different kinds of tools and technology