SentiNental

SentiNental is an application that allows users to track their daily moods. The app employs Natural Language Processing (NLP) to analyze the content of these entries, provides visual feedback on mood trends, and offers insights and suggestions based on detected mood patterns.

The developed natural language processing (NLP) model leverages the en_core_web_sm pipeline from the spaCy library for initial data processing, ensuring comprehensive linguistic analysis and feature extraction from the labeled Twitter sentiment data. The textual data is subsequently transformed into a numerical representation using the TfidfVectorizer from the widely employed scikit-learn library, thereby enabling the conversion of text data into a meaningful numeric format suitable for further analysis. The model is trained using a linear Support Vector Regressor (SVR), allowing for the generation of continuous output scores corresponding to distinct emotional categories derived from the processed Twitter data. This robust approach facilitates the assessment of sentiment nuances across multiple emotional dimensions, thereby contributing to a comprehensive understanding of the sentiment landscape within the Twitter dataset.

Video Link : https://www.loom.com/share/a854ce4c7bf74561bf53acd7e2f5cc79?sid=8fc5a8f4-db85-42de-b6f9-cad33cc5bf40

Table of Contents

• Getting Started
  • Prerequisites
  • Installation
• Running the App
  • Frontend (React.js)
  • Backend (Flask)
• Usage

Getting Started

Prerequisites

Before you begin, make sure you have the following software and tools installed:

• Node.js for running the React.js frontend.
• Python for the Flask backend.
• NLP libraries (e.g., spaCy or NLTK) for sentiment analysis.
• A database management system for data storage.
• Required dependencies listed in the requirements.txt file.

Installation

1. Clone this repository to your local machine:

   git clone https://github.com/Duyoofmp/SentiNental.git
   cd SentiNental

2. Install the required dependencies for the frontend:

   cd frontend
   npm install

3. Install the required dependencies for the backend:

   cd backend
   pip install -r requirements.txt

Running the App

Frontend (React.js)

1. Navigate to the frontend directory:

   cd frontend

2. Start the React app:

   npm start

   This will run the app in development mode. Open http://localhost:3000 to view it in your browser.

Backend (Flask)

1. Open a new terminal and navigate to the backend directory:

   cd backend

2. Start the Flask app:

   python flask_app.py

The Flask app for API.

Usage

1. Sign up or log in to your user profile.

2. Write or speak about your day's experiences in the app.

3. MoodTracker will analyze your entries and provide visual feedback on mood trends.

4. Receive insights and suggestions based on detected mood patterns.

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