📱💬 Crunchyroll Review Sentiment Analysis 📱💬

⭐ Project Overview ⭐

This project analyzes the sentiments of reviews for the Crunchyroll app on the Google Play Store 📊. Using Natural Language Processing (NLP) and Machine Learning, we aim to classify reviews as positive, neutral, or negative.

✨ Objectives ✨

• Understand user sentiment: Learn how to create a sentiment analysis model and implement it in a local Streamlit app.
• Drive business decisions: Listen to user feedback, understand criticism, and improve the app's performance and features.

🚀 Tech Stack 🚀

• Python : for computation and modeling.
• Streamlit : for an interactive web application.
• Scikit-Learn : for logistic regression, random forest, and TF-IDF vectorization.
• NLTK 🧠 for text preprocessing and analysis.

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📌 Key Features 📌:

• Sentiment Classification: Automatically classifies reviews as positive, neutral, or negative.
• Real-Time Analysis: Enter any review text and get sentiment analysis instantly.
• Data Visualization: Visualize sentiment distribution of Crunchyroll reviews.

Feel free to explore and contribute! 😊