This project focuses on Twitter Sentiment Analysis, utilizing Python to process and analyze Twitter data. It aims to gauge public opinion and sentiment on various topics by examining tweets. The core of the project involves applying Natural Language Processing (NLP) techniques and machine learning algorithms to classify tweets as positive, negative, or neutral. This approach provides valuable insights into public sentiment, useful for market analysis, political campaigns, and social research. The system leverages Python's powerful libraries, like NLTK and Pandas, for data handling and analysis, making it an effective tool for understanding and interpreting the vast amount of data generated on Twitter daily. This project is particularly relevant for those interested in data science, social media analytics, and understanding public opinion trends.
Twitter API_key and API_secret_key is required to execute this python program