Online Learning Sentiment Analysis Web App is a solution for analyzing public opinions on e-learning platforms. This tool empowers users with real-time insights, aiding e-learning providers in making informed decisions and enhancing user engagement.
📝 Table of Contents
🌐 About the Web Application
This web application utilizes advanced sentiment analysis techniques to interpret public sentiment towards online learning platforms. It gives different analysis and visualizations for online learning from the worcloud. Developed with Python, Streamlit, and Tweepy, it features:
- Real-time Twitter data analysis.
- Sentiment analysis with natural language processing.
- Enhanced data accuracy and fast response times.
- Twitter API integration for live data retrieval.
- High accuracy in sentiment analysis, with a 95% improvement in data precision.
- Streamlit-based interactive and responsive frontend.
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git clone /~https://github.com/aninda20/online-learning-sentimental-analysis-webapp.git
- Python
- Streamlit
- Natural Language Processing
- Main Page:
- Count Plot:
- Pie Chart of Sentiments:
- Tweets Visualization:
- AI Wordcloud:
