Skip to content

This repository contains a WhatsApp Chat Analyzer built using Machine Learning (ML) techniques. The goal of this project is to analyze WhatsApp chat logs to extract meaningful insights, generate visualizations, and uncover patterns in communication behavior.

Notifications You must be signed in to change notification settings

VaibhavVermaa16/Whatsapp-chat-analyser

Repository files navigation

Whatsapp-chat-analyser

This repository contains a WhatsApp Chat Analyzer built using Machine Learning (ML) techniques. The goal of this project is to analyze WhatsApp chat logs to extract meaningful insights, generate visualizations, and uncover patterns in communication behavior.

Table of Contents

  • Features
  • Installation
  • Usage
  • Examples
  • Technologies Used
  • Contributing
  • Contact

Features

  • Message Frequency: Track message frequency over time to identify periods of high and low activity.
  • Word Cloud: Generate word clouds to visualize the most commonly used words in the chat.
  • User Statistics: Extract user-specific statistics, such as the number of messages sent, average message length, and active hours.
  • Emoji Analysis: Analyze the usage of emojis to understand emotional expression.
  • Activiy : Analysis of active members on group.
  • Emoji Frequence: Track of most used emojis in the chat.

Installation

Prerequisites

  • Python 3.7 or higher
  • pip (Python package installer)

Steps

  • Clone the repository: https://github.com/VaibhavVermaa16/Whatsapp-chat-analyser.git cd whatsapp-chat-analyzer
  • Create a virtual environment (optional but recommended): python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate
  • Install the required dependencies: pip install -r requirements.txt

Usage

  • Export your WhatsApp chat as a text file and save it in the main directory.
  • Run the analysis script: streamlit run main.py
  • Upload the chat file on the web page.

Technologies Used

  • Python: The primary programming language for the project.
  • Pandas: For data manipulation and analysis.
  • Numpy: For numerical computations.
  • Matplotlib/Seaborn: For data visualization.
  • Streamlit: For web application
  • Wordcloud: For creating word cloud.

Contributing

Contributions are welcome! Please follow these steps:

  1. Fork the repository.
  2. Create a new branch: git checkout -b feature/your-feature
  3. Make your changes and commit them. git commit -m 'Add some feature'
  4. Push to the branch: git push origin feature/your-feature
  5. Open a pull request.

Contact

For any inquiries or feedback, please open an issue or contact me at [email protected].

About

This repository contains a WhatsApp Chat Analyzer built using Machine Learning (ML) techniques. The goal of this project is to analyze WhatsApp chat logs to extract meaningful insights, generate visualizations, and uncover patterns in communication behavior.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published