Restaurant Review Analysis System

Project Overview

This project aims to build a comprehensive system for collecting and analyzing restaurant reviews. The system will:

1. Collect reviews from various platforms.
2. Analyze the sentiment of the reviews to generate a rating.
3. Provide explanations for the generated ratings.
4. Create a word cloud highlighting key themes from the reviews.
5. Analyze restaurant images to classify them based on suitability for different dining experiences (e.g., family, casual, date) and suggest improvements.

Features

• Review Collection: Gather restaurant reviews from sources like Yelp and Google Reviews.
• Sentiment Analysis: Analyze the sentiment of the reviews to derive a rating.
• Rating Explanation: Provide detailed explanations for the generated ratings.
• Word Cloud Generation: Identify common themes in the reviews to create a word cloud.
• Image Analysis: Classify the restaurant type based on images and suggest improvements.

Technology Stack

• Python: Main programming language.
• Gemini Pro API: Used for NLP and image analysis tasks.
• NLP Libraries: For additional natural language processing.
• Image Processing Libraries: For analyzing restaurant images.
• Web Scraping Tools: To collect reviews from various platforms.

Installation

Prerequisites

• Python 3.7 or higher
• API key for Gemini Pro

Setup

1. Clone the repository:

   git clone https://github.com/PhenomSG/Sentiment_Analysis_Using_NLP.git
   cd restaurant-review-analysis

2. Create and activate a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install the required packages:

   pip install -r requirements.txt

4. Set up your Gemini Pro API key:

   export GEMINI_API_KEY='your_gemini_api_key'

Usage

Collecting Reviews

To collect reviews from a source (e.g., Yelp), use the provided collect_reviews_from_source function:

from review_collector import collect_reviews_from_source

reviews = collect_reviews_from_source('yelp', 'restaurant_id')

Analyzing Reviews

To analyze sentiment and generate a rating:

from review_analysis import sentiment_analysis, aggregate_ratings, gemini_pro_explain_rating

ratings = sentiment_analysis(reviews, model='gemini_pro')
overall_rating = aggregate_ratings(ratings)
explanation = gemini_pro_explain_rating(reviews, overall_rating)

Generating a Word Cloud

To generate a word cloud from the reviews:

from word_cloud_generator import extract_keywords, generate_word_cloud

word_cloud_data = extract_keywords(reviews)
generate_word_cloud(word_cloud_data)

Analyzing Images

To classify restaurant type and suggest improvements based on images:

from image_analysis import classify_restaurant_type, assess_image_quality

for image in restaurant_images:
    category = classify_restaurant_type(image, model='gemini_pro')
    improvements = assess_image_quality(image, model='gemini_pro')
    print(f"Category: {category}, Improvements: {improvements}")

Directory Structure

restaurant-review-analysis/
│
├── README.md                # Project overview and instructions
├── requirements.txt         # List of dependencies
├── collect_reviews.py       # Functions for collecting reviews
├── review_analysis.py       # Functions for analyzing reviews
├── word_cloud_generator.py  # Functions for generating word clouds
├── image_analysis.py        # Functions for analyzing images
└── main.py                  # Main script to run the analysis

License

This project is licensed under the MIT License. See the LICENSE file for details.