FeedbackFinder - Product Review Analyzer

FeedbackFinder is a robust tool designed to help you uncover sentiments and opinions within product reviews. Leverage this data to enhance your products and services based on customer feedback.

Features

• Sentiment Analysis: Predict sentiments (positive or negative) of product reviews using different machine learning models.
• Bulk Predictions: Upload a CSV file containing multiple reviews for bulk prediction.
• Single Review Analysis: Enter a single product review for instant sentiment prediction.
• Text Preprocessing: Customize preprocessing options such as stemming, stopword removal, lowercase conversion, punctuation removal, and lemmatization.
• Download Predictions: Export sentiment prediction results as a CSV file.
• Feedback Collection: Gather user feedback to improve the application.

Installation

1. Clone the repository:

   git clone github.com:supriya811106/Product-Review-Analyzer.git

2. Navigate to the project directory:

   cd Product-Review-Analyzer

3. Create a virtual environment and activate it:

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

4. Install the required packages:

   pip install -r requirements.txt

Running the Application

1. Start the Streamlit application:

   streamlit run app.py

2. Open your web browser and navigate to http://localhost:8501 to access the application.

Usage

Sentiment Analysis

1. Select a Model: Choose a machine learning model for sentiment prediction (XGBoost, RandomForest, LogisticRegression).
2. Upload Reviews: Upload a CSV file containing product reviews for bulk prediction or enter a single review in the text area.
3. Preprocess Text: Choose text preprocessing options from the sidebar.
4. Predict Sentiment: Click the "Predict" button to get sentiment predictions.
5. Download Results: Download the prediction results as a CSV file if a file was uploaded.

How It Works

1. Select a Model: Choose a machine learning model for sentiment analysis.
2. Upload Reviews: Upload a CSV file with product reviews or enter a single review.
3. Preprocess Text: Select text preprocessing options such as stemming, stopword removal, etc.
4. Predict Sentiment: Get sentiment predictions and download the results.
5. Analyze Feedback: Use the insights to improve your products and services.

Feedback

1. Provide Feedback: Select how helpful you found the insights.
2. Share Comments: Optionally, provide additional comments or suggestions.
3. Submit: Enter your name and email (optional) and submit your feedback.

Customization

• Custom CSS: Modify the static/style.css file to change the look and feel of the application.
• Logo: Replace static/logo.png with your own logo.

Acknowledgements

Thank you for using FeedbackFinder! We hope it helps you gain valuable insights from your product reviews.