Amazon Reviews Sentiment Analyser

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Overview

This project focuses on sentiment analysis using machine learning and natural language processing techniques. The goal is to develop a Streamlit app capable of analyzing sentiments in various scenarios, including single-line reviews, multiple reviews from CSV files, and product reviews from Amazon URLs.

Project Structure

• B8_Amazon: Contains Jupyter notebooks with exploratory data analysis and model development.
• reviewscrapper.py: Includes Python scripts for web scraping reviews for a certain URL.
• review_analyzer.py: Houses the Streamlit app code for interactive sentiment analysis.
• models.p: Stores serialized models for sentiment analysis.
• requirements.txt: Lists the project dependencies for reproducibility.
• config.toml: Configuration for the Streamlit app theme.

Setup

1. Clone the repository:

   git clone https://github.com/amri-tah/Amazon-Review-Sentiment-Analysis.git

2. Navigate to the project directory:

   cd Amazon-Review-Sentiment-Analysis

3. Install dependencies:

   pip install -r requirements.txt

4. Open terminal and run the Streamlit app:

   streamlit run review_analyzer.py

Usage

1. Explore and run Jupyter notebook B8_Amazon.ipynb folder for data analysis and model development.

2. Execute Python scripts in the reviewscrapper.py for web scraping.

3. Run the Streamlit app for interactive sentiment analysis:

   streamlit run review_analyzer.py