Sentiment Analysis, also known as Opinion Mining, is a computational process to determine whether a piece of content is positive, negative, or neutral. It is widely used to gauge public views on various subjects like products, events, and political figures. In this post, the focus is on extracting 1000 tweets about the Prime Minister of India, Narendra Modi, and performing sentiment analysis using Python libraries like Tweepy and TextBlob. Tweepy is used to access the Twitter API, while TextBlob helps in processing textual data, including sentiment analysis. The sentiment classifier in TextBlob assigns a polarity value between -1.0 and 1.0 to determine the sentiment as negative, neutral, or positive.