Sentiment Analysis Web App

A Streamlit Python web application to analyze sentiment in CSV files and add sentiment values to the data.

Features

• 📊 Upload CSV files and analyze sentiment
• 🔍 Automatic sentiment classification (Positive, Negative, Neutral)
• 📈 Polarity and Subjectivity scores
• 📥 Download results as CSV
• 🎨 User-friendly interface

Installation

1. Clone or download this repository

2. Install the required dependencies:

pip install -r requirements.txt

3. Download TextBlob corpora (required for sentiment analysis):

python -m textblob.download_corpora

Usage

1. Run the Streamlit application:

streamlit run main.py

2. Open your browser and navigate to the URL shown in the terminal (usually http://localhost:8501)

3. Upload a CSV file containing text data

4. Select the column containing text to analyze

5. Click "Analyze Sentiment" to process the data

6. Download the results as a CSV file with added sentiment columns:

   • polarity: Sentiment polarity score (-1 to 1)
   • subjectivity: Subjectivity score (0 to 1)
   • sentiment: Sentiment label (Positive, Negative, Neutral)

CSV Format

Your CSV file should contain at least one column with text data. Example:

id	text
1	I love this product!
2	This is terrible.
3	It's okay.

Sentiment Scores

• Polarity: Ranges from -1 (very negative) to 1 (very positive)
• Subjectivity: Ranges from 0 (objective) to 1 (subjective)
• Sentiment Label:
  • Positive (polarity > 0.1)
  • Negative (polarity < -0.1)
  • Neutral (polarity between -0.1 and 0.1)

Technologies Used

• Streamlit: Web application framework
• Pandas: Data manipulation and analysis
• TextBlob: Natural language processing and sentiment analysis

Requirements

• Python 3.7 or higher
• See requirements.txt for package versions

License

This project is created for educational purposes.