metadata
title: Dark Pattern Detector
emoji: 🛡️
colorFrom: purple
colorTo: red
sdk: static
pinned: true
tags:
- dark-patterns
- nlp
- consumer-protection
- distilbert
Dark Pattern Detector 🛡️
An interactive NLP classification engine designed to detect deceptive UI copy, artificial scarcity, and manipulative e-commerce patterns.
- GitHub Repository: JayanGupta/Dark-Pattern-Detection
- Author: Jayan Gupta
🎯 What are Dark Patterns?
Dark patterns are user interface designs crafted to trick users into doing things they might not otherwise do (e.g. buying unwanted add-ons, signing up for disguised recurring subscriptions, or agreeing to invasive tracking).
📋 Detected Taxonomies
This tool identifies manipulative patterns across industry-standard taxonomies:
- Urgency & Scarcity: Artificial countdown timers and fake low-stock alerts.
- Misdirection: Using visual hierarchy or pre-checked checkboxes to steer users toward a specific choice.
- Social Proof Exploitation: Synthetic activity notifications ("34 people looking at this right now").
- Forced Continuity: Easy one-click signups combined with labyrinthine cancellation flows.
- Confirm-shaming: Emotionally manipulative copy on opt-out buttons ("No thanks, I hate saving money").
- Hidden Costs: Unannounced fees revealed only on the final checkout screen.
🛠️ Development & Transparency Note
Designed and developed by Jayan Gupta. The taxonomy and heuristics are based on FTC consumer protection guidelines and academic dark-pattern datasets. AI assistants were used for prototyping and documentation structuring.