Sentiment analysis refers to analyzing an opinion or feelings about something using data like text or images, regarding almost anything. Due to the fast growth of World Wide Web the online communication has increased. In recent times the communication focus has shifted to social networking. In order to enhance the text methods of communication such as tweets, blogs and chats, it is necessary to examine the emotion of user by studying the input text. Nowadays, people express their personal interests, feelings, and opinions on social media. Online reviews are posted by customers for the products and services on offer at a website portal. This has provided impetus to substantial growth of online purchasing making opinion analysis a vital factor for business development. To analyze such text and reviews sentiment analysis is used. Sentimental analysis helps companies in their decision-making process. For instance, if public sentiment towards a product is not so good, a company may try to modify the product or stop the production altogether in order to avoid any losses. There are many sources of public sentiment e.g. public interviews, opinion polls, surveys, etc. However, with more and more people joining social media platforms, websites like Facebook and Twitter can be parsed for public sentiment. In this project, we will perform sentiment analysis to evaluate coffee preferences from two companies Tim Horton’s and Starbucks. Analysis will be performed based on the Twitter data collected from twitter API, and we will be using Hashtags associated with each company. We will be searching for a specific keywords that would describe coffee and associated sentiment. In our work, we will be collecting these sentiments and classify polarity of sentiments in these opinions with respect to Positive, Negative or Neutral