Movie Review Sentiment Analysis

This project is a sentiment analysis tool for movie reviews using machine learning. The model classifies reviews as positive or negative based on the text content.

Introduction

This project uses a dataset of movie reviews to train a machine learning model that can predict the sentiment of new reviews. The project includes scripts for creating the dataset, training the model, and predicting sentiments.

Setup

Prerequisites

• Python 3.x
• pip (Python package installer)
• Virtualenv (optional but recommended)

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/moviereview-sentiment-analysis.git
   cd moviereview-sentiment-analysis

2. Create a virtual environment:

   python -m venv env

3. Activate the virtual environment:

   • On Windows:

     .\env\Scripts\activate

   • On macOS/Linux:

     source env/bin/activate

4. Install the required packages:

   pip install -r requirements.txt

Usage

Creating the Dataset

Run the script to create the dataset:

python create_dataset.py

This will generate a movie_reviews.csv file with sample movie reviews and their sentiments.

Training the Model

Run the script to train the model and make predictions:

python test.py

Follow the prompts to enter your own movie reviews and get sentiment predictions.

Contributing

Contributions are welcome! Please fork the repository and create a pull request with your changes.

Steps to Contribute

1. Fork the repository.
2. Create a new branch for your feature or bugfix.
3. Make your changes.
4. Commit and push your changes to your fork.
5. Create a pull request to the main repository.