Deceptive Patterns by Kaggle | Ecommerce and Consumer Trends

About this Dataset

Deceptive Patterns

Dark Pattern Detection Dataset

This dataset is designed to aid in the detection of dark patterns in e-commerce websites, specifically targeting fake reviews and fake star ratings. It consists of two files that help classify and analyze deceptive online practices:

Files Included

patterns.csv – Contains various dark pattern instances with textual or numerical representations.
pattern_classification.csv – Maps the identified patterns to specific categories, enabling supervised learning approaches for classification.

Dataset Usage

Identifying and classifying dark patterns in e-commerce.
Training machine learning models to detect fake reviews and ratings.
Enhancing consumer protection by flagging deceptive practices.

Potential Applications

AI-driven browser extensions to warn users about suspicious reviews.
E-commerce trust and safety monitoring systems.
Research on manipulative online behavior.

This dataset is valuable for researchers and developers working on fraud detection, AI ethics, and consumer protection in digital marketplaces. 🚀

Tables

Pattern Classifications

@kaggle.akashnath29_deceiptive_patterns.pattern_classifications

49.28 KB
2700 rows
2 columns


CREATE TABLE pattern_classifications (
  "pattern_string" VARCHAR,
  "classification" DOUBLE
);

Patterns

@kaggle.akashnath29_deceiptive_patterns.patterns

23.22 KB
416 rows
8 columns


CREATE TABLE patterns (
  "pattern_string" VARCHAR,
  "comment" VARCHAR,
  "pattern_category" VARCHAR,
  "pattern_type" VARCHAR,
  "where_in_website" VARCHAR,
  "deceptive" VARCHAR,
  "website_page" VARCHAR,
  "industry_type" VARCHAR
);