Tweet Sentiment Analysis

This project analyzes tweet sentiments (HAPPY or SAD) using a trained machine learning model. It includes a front-end interface for displaying predictions and a back-end for model inference and training.

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Project Structure

├── app.py
├── basics.py
├── LATEST_NOV.pkl
├── model_training.ipynb
├── Procfile
├── README.md
├── requirements.txt
├── static
│   ├── class_distribution.jpg
│   ├── confusion_matrix.jpg
│   ├── distribution_curve.jpg
│   ├── happy.jpg
│   ├── learning_curve.jpg
│   ├── precision_recall_curbve.jpg
│   ├── ROC.jpg
│   └── sad.jpg
├── templates
│   ├── after.html
│   └── home.html

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Features

1. Sentiment Prediction:

   • Predicts if a tweet expresses a HAPPY or SAD sentiment.
   • Displays the result visually using images or GIFs.

2. Model Training:

   • model_training.ipynb includes code for training the sentiment analysis model.
   • Evaluation metrics such as confusion matrix, precision-recall curve, ROC curve, etc., are included.

3. Front-End:

   • Uses Flask and HTML templates for user interaction.
   • Provides a clean and interactive UI for entering tweets and viewing predictions.

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Installation and Setup

Prerequisites

• Python 3.8 or above
• pip package manager
• Virtual environment (venv)

Step 1: Clone the Repository

git clone <repository_url>
cd <repository_folder>

Step 2: Create and Activate a Virtual Environment

• Create the virtual environment

python3 -m venv venv

• Activate the virtual environment

source venv/bin/activate

Step 3: Install Required Dependencies

Install the dependencies listed in requirements.txt

pip install -r requirements.txt

Step 4: Run the Flask Application

Start the Flask server by running

python app.py

The app will be accessible at http://10.42.0.198:5000/

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How to Run

• Open your browser and go to http://10.42.0.198:5000/.
• Enter a tweet in the input field on the homepage.
• Submit the tweet to analyze its sentiment.
• View Results:

The app will display whether the sentiment is HAPPY or SAD, accompanied by a visual representation (image).

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