As we all know social media is a growing industry in the current world. People of every age are using social media directly or indirectly. Millions of people are sharing their thoughts on Twitter day by day. Every tweet has its own characteristics and expressions. The technologies I have used for analyzing the datasets of Twitter are data mining and NLP with Python. After collecting the data, we have trained it and made the tweets capable of testing, so it can give us the proper sentimental output. This paper will help us to understand the sentiment analysis techniques and also helps us to extract sentiments from Twitter datasets. The Twitter datasets collected from Kaggle and other sources. In this paper, we have focused on the comparative study of the different algorithms as well as on techniques.
