AI Sentiment Analysis App by Hira SaleemAI Sentiment Analysis App by Hira Saleem

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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