AI Sentiment Analysis App

Hira Saleem

Completed work

Fullstack Engineer

Flask

JavaScript

Python

Artificial Intelligence

AI Sentiment Analysis App

The AI Sentiment Analysis App is a machine learning-powered web application that analyzes text input and determines its sentiment as positive, negative, or neutral. It utilizes natural language processing (NLP) techniques to provide accurate sentiment classification.

Features

Real-Time Sentiment Analysis – Instantly classify text as positive, negative, or neutral.

User Authentication – Secure login and user management system.

API Support – REST API endpoints for integration with other applications.

Data Visualization – Display sentiment trends using charts.

Database Storage – Store and manage analyzed texts for future reference.

Scalable and Secure – Designed for scalability with robust security measures.

Technologies Used

Backend: Python, Flask

Machine Learning: Watson NLP / NLTK / TextBlob

Frontend: HTML, CSS, JavaScript, Bootstrap

Database: PostgreSQL / MongoDB

Authentication: JWT (JSON Web Token)

Deployment: Docker, Heroku/AWS/GCP

Project Structure

AI-Sentiment-Analysis-App/
├── models/             # Sentiment analysis models
├── routes/             # API routes for text processing
├── templates/          # Frontend templates
├── static/             # Static assets (CSS, JS, images)
├── app.py              # Main application file
├── config/             # Configuration files (DB, authentication)
├── requirements.txt    # Python dependencies
├── README.md           # Project documentation

Getting Started

Follow these steps to set up the project locally:

1. Clone the Repository

git clone https://github.com/HSk2703/AI-Sentiment-Analysis-App.git
cd AI-Sentiment-Analysis-App

2. Create a Virtual Environment

python3 -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install Dependencies

pip install -r requirements.txt

4. Set Up Environment Variables

Create a .env file in the root directory and configure the necessary environment variables:

FLASK_APP=app.py
FLASK_ENV=development
DATABASE_URL=your_database_connection_string
SECRET_KEY=your_secret_key

5. Run the Application

flask run

6. Access the Application

Open your browser and navigate to:

👉 http://127.0.0.1:5000/

API Endpoints

Method Endpoint Description POST /analyze Analyze text sentiment GET /history Retrieve previously analyzed data

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Completed work

Posted Oct 13, 2024

AI Sentiment Analysis App uses NLP to classify text sentiment as positive, negative, or neutral with machine learning for accurate analysis.

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AI Sentiment Analysis App

AI Sentiment Analysis App

Features

Technologies Used

Project Structure

Getting Started

1. Clone the Repository

2. Create a Virtual Environment

3. Install Dependencies

4. Set Up Environment Variables

5. Run the Application

6. Access the Application

API Endpoints

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