Social media has become an indispensable part of social life. It influences the beliefs, values, and attitudes of people, as well as their intentions and behaviours. Social media acts not only as a platform for personal communication, but also, as a means for communicating opinions about products and services or even political and general events among its users. Due to its widespread and popularity, a huge amount of user reviews or opinions are being generated and shared daily on social media. Therefore, converting social media content into information, key concepts, and themes is crucial for generating knowledge and formulating strategies to support operational, managerial, and strategic decision making. Opinion mining and Sentiment analysis are the formalization for studying and constructing opinions and sentiments. The current paper aims at studying and providing the comparison of different methods of sentiment analysis used for extracting the polarity (positive, negative or neutral) of social media dataset.