Comparison of Twitter Sentimental Analysis Using Various Classifier

Abstract

The Social Media Platform has emerged recently as the most powerful platforms for people to give their opinion and influence of almost each and every part of everybody’s day to day life. These opinions of people matters lot to analyze how propagation of the information impacts this world around us in the socials media platforms like twitter and facebook. Sentiment analysis of the tweets and facebook comments help us in understanding the polarities and the inclination of people because of a specific agenda, special topics, a product or any topic concerning them. The areas where this sentiment analysis is widely used are public elections, promotion of a movie, and analysis of a brand new product. In this project we have used the different online platforms to extract the available live tweet and comments and perform sentiment analysis. The aim basically is to analyze the sentimental score in the noisy twitter rest and facebook comments. This paper gives reports on the sentimental analysis of extracting huge number of the tweet and facebook comments. Final results classify comments and tweets into positive and negative towards that particular topic. Also, we discussed the different possible techniques to carry out sentimental analysis on the extracted datum. In the implemented system, texts from social media are collected and opinion mining is done on these texts. According to the outcome of the sentiment analysis on these pieces of text various suggestions can be made to the user. Taking an example, opinion mining can be done on dataset present for the patients and consumer’s opinions on the various clinical treatment and medicines. These outcomes gives information for the use of various hospitals, pharmaceutical industry.