💬 Sentiment Analysis using VADER

An NLP-based sentiment analysis project that uses VADER (Valence Aware Dictionary and sEntiment Reasoner) to analyze user-provided text and classify it as Positive, Negative, or Neutral.

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📌 Overview

This project performs sentiment analysis on text input using VADER, a lexicon and rule-based sentiment analysis tool designed for understanding the sentiment of text.

The program takes user input, calculates sentiment scores, and displays the overall sentiment category.

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✨ Features

• Interactive user input
• Calculates positive, negative, and neutral sentiment scores
• Classifies text into:
  • 😊 Positive
  • 😞 Negative
  • 😐 Neutral
• Continuous analysis until the user exits
• Simple command-line interface

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🛠️ Technologies Used

• Python 🐍
• VADER Sentiment
• Natural Language Processing (NLP)

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📂 Project Structure

Sentiment-Analysis-VADER
│
├── Sentiment_analysis.py
├── requirements.txt
├── README.md
└── .gitignore

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⚙️ Installation

Clone the repository:

git clone https://github.com/Sathyabyte/Sentiment-Analysis-VADER.git

Install dependencies:

pip install -r requirements.txt

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🚀 Usage

Run the program:

python Sentiment_analysis.py

Enter any sentence when prompted.

Example:

Enter a sentence: I love learning Artificial Intelligence

Overall Sentiment: Positive 😊

To exit:

quit

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📊 Sentiment Scores

The analyzer provides:

• Negative score
• Neutral score
• Positive score
• Compound sentiment score

The compound score determines the final sentiment classification.

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🔮 Future Improvements

• Add graphical user interface (GUI)
• Analyze text from social media platforms
• Add sentiment visualization
• Support multiple languages

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👩‍💻 Author

Sathyabyte

BCA (Hons) Student | Data Science + AI/ML