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WhatsApp Wrapped

Spotify Wrapped-style analytics for WhatsApp group chats

Upload interface with WhatsApp-themed gradient

A beautiful full-stack analytics platform that transforms WhatsApp chat exports into stunning visual insights. Features AI-powered topic modeling, sentiment analysis, personality classification, and temporal pattern detection with a modern, interactive UI.

ROLEFull Stack Developer
Next.jsReactscikit-learnVADER SentimentLDA
Big picture statistics slide
Big picture statistics slide

Tech Stack

The engine behind the experience

Next.jsReactscikit-learnVADER SentimentLDATypeScriptFastAPIPythonPandasRegex

OVERVIEW

WhatsApp Wrapped is a comprehensive analytics platform inspired by Spotify Wrapped, designed to transform your WhatsApp group chat exports into beautiful, shareable insights. The application consists of a Next.js frontend with smooth animations and a FastAPI backend that performs deep analysis on chat data. The system features 10+ specialized analytics modules including basic statistics (message counts, word counts, active days), temporal analysis (peak hours, chronotype detection, busiest days), personality classification (15+ personality types from Spammer to Silent Observer), emoji usage patterns, media sharing insights, code snippet detection, VADER-based sentiment analysis, and LDA topic modeling optimized for Hinglish conversations. The frontend delivers a stunning 11-slide experience with Framer Motion animations, swipe gestures, and shareable summary cards. The backend uses advanced NLP techniques including scikit-learn's Latent Dirichlet Allocation for topic discovery, VADER sentiment analysis for emotional timelines, and custom pattern matching for personality classification. Built with privacy in mind, the platform processes chat data ephemerally without storing conversations. The parser handles multiple WhatsApp export formats and date patterns, making it compatible with various chat export styles. The application provides insights into group dynamics, conversation topics, emotional trends, and individual participation patterns.