---
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](https://github.com/JayanGupta/Dark-Pattern-Detection)
- **Author**: [Jayan Gupta](https://huggingface.co/Jayan12321)

---

## 🎯 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).

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## 📋 Detected Taxonomies
This tool identifies manipulative patterns across industry-standard taxonomies:
1. **Urgency & Scarcity**: Artificial countdown timers and fake low-stock alerts.
2. **Misdirection**: Using visual hierarchy or pre-checked checkboxes to steer users toward a specific choice.
3. **Social Proof Exploitation**: Synthetic activity notifications ("34 people looking at this right now").
4. **Forced Continuity**: Easy one-click signups combined with labyrinthine cancellation flows.
5. **Confirm-shaming**: Emotionally manipulative copy on opt-out buttons ("No thanks, I hate saving money").
6. **Hidden Costs**: Unannounced fees revealed only on the final checkout screen.

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## 🛠️ 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.