- Developed an application to perform sentiment analysis on Twitter data using usernames and hashtags, analyzing the last 20 tweets for each input.
- Implemented features to allow both automatic fetching of tweets and manual text input for customized sentiment evaluation.
- Utilized natural language processing (NLP) techniques to classify emotions and sentiments, providing insights into public opinion trends.
- Integrated a user-friendly interface for easy interaction, allowing users to quickly visualize sentiment results and trends based on real-time data. -- Technologies Used: Python, Twitter API, Natural Language Processing (NLP), Sentiment Analysis Libraries (e.g., TextBlob, NLTK), Flask, HTML/CSS, JavaScript
