🌟 IMDb Sentiment Analysis 🌟

Dive into the world of movie reviews and analyze sentiments using Python! 🎥🍿

📌 Introduction

This repository contains a Python-based Sentiment Analysis tool which classifies IMDb movie reviews into positive (👍) and negative (👎) sentiments. Whether you're a movie buff, a data enthusiast, or someone who just loves playing with texts, this tool is for you!

📂 Structure

.
├── IMDB
│   ├── Train.csv
│   ├── Valid.csv
│   ├── Test.csv
└── text_analysis.py

🚀 Getting Started

🛠 Prerequisites

• Make sure you have Python3 installed:

python3 --version

⬇ Installation

1. Clone this repository:

git clone [(https://github.com/reecebaileyy/Sentiment-Analysis-for-Text.git)]
cd Sentiment-Analysis-for-Text

2. Install required libraries:

pip install pandas numpy matplotlib nltk textblob scikit-learn wordcloud

🏃 Running the Tool

python3 text_analysis.py

📊 Outputs

• Displayed filenames in the IMDB folder.
• Pie chart 🥧 showing label distribution.
• Word clouds ☁️ for positive and negative reviews.
• Performance metrics 📈 of the model on validation and test datasets.

✨ Future Updates

• Integrate more advanced NLP models for better accuracy.
• Add a GUI interface.
• Allow custom reviews for prediction.

🤝 Contribution

Feel free to fork this project, raise issues, and submit Pull Requests.

🙌 Acknowledgements IMDb for the dataset. Textblob and NLTK for processing tools.