Main Article Content
Abstract
Social media is a platform which signifies the viewpoint of people about government, product, and services. Classifying the views in term of positive or negative division from social media text is task of sentimental analysis. Twitter is one such online social networking website where people can post their views about something. This platform help people to share as well as found views on the topics which are going around the world. Twitter is a huge platform with more than 300 million users. So, tweets can be used as a resource for mining views of people. Process of classifying views as positive, negative or neutral is known as sentimental analysis. Saying people tweet about everything and nothing is not an overemphasis. We need a quicker identification method to classify the information that can be used for training in order to construct the systems to twitter sentimental analysis on any given topic. In this project, we progress a method for building such data using Twitter (for example: #excellent #Nature Lover #epic failure) to identify emotional messages that can be used to classify sentiment.