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Data Science · Mini Project

WhatsApp Chat Analyser with Sentiment

Turns an exported chat file into activity stats, word clouds and mood

1-2 weeks build

Overview

Upload a chat exported from WhatsApp's own Export Chat option and the app parses every message into a timestamped table, handling both 12- and 24-hour formats. It then charts who talks most and when, builds word and emoji clouds, and scores each message with VADER so you can follow the group's mood over time. Everything runs locally and nothing is uploaded anywhere.

What makes it stand up

  • 01Regex parser for Android and iOS export formats
  • 02Per-member message, word, media and link counts
  • 03Hourly and weekday activity heatmaps
  • 04Word and emoji clouds with Hinglish stop-word filtering
  • 05VADER sentiment timeline per member and for the whole chat

Module breakdown

  1. 01

    Parser

    Splits raw export lines into date, author and message columns.

  2. 02

    Statistics

    Counts messages, words, media and links per participant.

  3. 03

    Timelines

    Daily, monthly and hour-by-weekday activity charts.

  4. 04

    Text analysis

    Stop-word removal, word clouds and emoji frequency.

  5. 05

    Sentiment

    VADER compound scores rolled up by day and by member.

After this, you will be able to

  • Explain how the regex parser copes with different export formats
  • Defend the choice of a lexicon-based sentiment model
  • Demo the dashboard on a freshly exported chat

Technology stack

  • Python
  • Pandas
  • NLTK
  • Matplotlib
  • Streamlit

Complete kit

₹5,199₹8,799
-41%

Delivered in under 48 hours

Level
Mini Project
Domain
Data Science
Build time
1-2 weeks
Difficulty

You receive

  • Complete, commented source code
  • 60-90 page project report (IEEE format)
  • Editable presentation deck
  • Architecture, ER and UML diagrams
  • Local setup and deployment guide
  • Sample dataset or seed data
  • Viva question bank with answers
  • One 45-minute walkthrough call
  • 30 days of doubt-clearing support
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