AWS Sentiment Analysis Project

This is a web-based sentiment analysis application that leverages AWS Comprehend to analyze the sentiment of user-provided text. The application is deployed on an AWS EC2 instance and built using Python (Flask), HTML, and the AWS SDK (Boto3).

Made for:
Machine Learning Cloud Computing (AIGC-5003)
Humber Polytechnic, AI and Machine Learning Postgraduate Program

---

🌐 Live Demo

Watch the full application walkthrough here: YouTube Demo

---

📌 Features

• User-friendly web interface for entering text
• Real-time sentiment analysis using AWS Comprehend
• Deployment-ready Flask backend on AWS EC2
• Secure SSH access and configurable AWS Security Groups
• Returns overall sentiment: Positive, Negative, or Neutral

---

🛠️ Technologies Used

• Frontend: HTML (index.html)
• Backend: Python + Flask (main.py)
• Sentiment Analysis: AWS Comprehend (comprehend.py)
• Deployment: AWS EC2, SSH, Security Groups
• Cloud SDK: Boto3

---

📂 Project Structure

.
├── main.py                  # Flask backend server
├── comprehend.py            # AWS Comprehend sentiment analysis logic
├── index.html               # Frontend UI
├── Sample Input.csv         # Sample input data
├── *.png                    # Screenshots
├── AWS Sentiment Analysis Project Documentation.pdf
└── README.md                # You're here!

---

📷 Screenshots

Screenshots provided include:

• Web UI showing sentiment results
• EC2 instance setup and SSH session
• Security Group rule allowing traffic on port 5000

---

🧠 How It Works

1. User Input
The user enters a sentence into the input text field on the web page.

2. Processing
Once the user clicks "Analyze Sentiment," the text is sent to the Flask backend. The backend uses AWS Comprehend to analyze the sentiment.

3. Output
The result (Positive, Negative, or Neutral) is returned and displayed on the refreshed web page.

---