Arpita N Sheelvanth
This project applies Natural Language Processing (NLP) techniques to WhatsApp chat data to generate meaningful insights.
The goal is to analyze conversations, identify usage patterns, and summarize chat behavior.
Natural Language Processing (NLP) is a field of Artificial Intelligence that enables computers to understand and process human language.
In this project, NLP is used to analyze text-based WhatsApp conversations.
- Import WhatsApp chat text file (.txt)
- Text Preprocessing (NLP): cleaning, tokenization, removing stopwords
- Word Frequency Analysis: most used words & phrases
- User Activity Analysis: who sends the most messages
- Time-based Analysis: messages per day/hour
- Sentiment Analysis (NLP): classify chat as Positive / Negative / Neutral
- Visual Analytics: charts & graphs for insights
- TypeScript, JavaScript
- HTML, CSS, Tailwind CSS
- NLP Libraries / APIs (for text preprocessing & sentiment analysis)
- Vite (build tool)
- Clone the repo
git clone https://github.com/ans006/WhatsappDataAnalytics.git
👉 You can edit this to suit your project idea. https://whatsapp-data-analyt-szo0.bolt.host