Social media is widely used for interactions among people in which they create, share, exchange information, opinions, and thoughts. Some social media websites as emerged as one the platforms to raise users’ opinions and influence the way any business is commercialized. These days, the applications of such analysis can be easily observed using public elections, movie promotions, brand endorsements, and many other fields. Opinions of people matter a lot to analyze how the propagation of information impacts the lives in a large-scale network like Twitter. In this paper, we can see different feature sets and machine learning classifiers to determine the best combination of sentimental analysis of tweets. The primary aim is to explore possible methods for analyzing sentiment scores in a noisy Twitter stream. This paper reports on the design of sentiment analysis, extracting vast twitter data such as tweets. We can also see various techniques to carry out a sentiment analysis on Twitter data in detail.