Skip to content

Mjsentiment/imdb-sentiment-app

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

2 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

🎬 IMDB Sentiment Predictor

This interactive web app analyzes movie reviews and predicts their sentiment—Positive 😊 or Negative 😞—using a trained machine learning model and natural language processing. Built with Streamlit, it includes real-time predictions, data visualization, and optional voice playback.


🔍 Features

  • ✅ Clean NLP preprocessing with BeautifulSoup, regex, and stopword removal
  • 🎓 Machine Learning using a scikit-learn classifier and TF-IDF vectorizer
  • 📊 Summary stats with visual feedback (positive/negative proportions)
  • 💬 Text-to-speech playback of predictions (browser-based voice)
  • 💾 Save and display recent reviews and predictions
  • 📁 Export all analyzed reviews to CSV

🚀 Try it Online

🖥️ Deploy your own version or use this repo with Streamlit Cloud.

Just make sure your main app script is correctly set in the app configuration (e.g., sentiment_webapp.py or app.py).


⚙️ Requirements

Install dependencies with: streamlit scikit-learn pandas beautifulsoup4 nltk pickle-mixin html5lib numpy requests streamlit==1.33.0 scikit-learn==1.4.1.post1 pandas==2.2.2 nltk==3.8.1 beautifulsoup4==4.12.3 dir

pip install -r requirements.txt
# imdb-sentiment-app

About

Analyze IMDB movie reviews using machine learning to predict positive or negative sentiment. Built with Streamlit and scikit-learn. Includes text-to-speech, CSV export, visual summaries, and review history.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors

Languages