Dark Patterns at Scale: Findings from a Crawl of 11K Shopping Websites
Arunesh Mathur et al, Princeton:
Dark patterns are user interface design choices that benefit an online service by coercing, steering, or deceiving users into making unintended and potentially harmful decisions. We present automated techniques that enable experts to identify dark patterns on a large set of websites. Using these techniques, we study shopping websites, which often use dark patterns these to influence users into making more purchases or disclosing more information than they would otherwise. Analyzing ∼53K product pages from ∼11K shopping websites, we discover 1,841 dark pattern instances, together representing 15 types and 7 categories. We examine the underlying influence of these dark patterns, documenting their potential harm on user decision-making. We also examine these dark patterns for deceptive practices, and find 183 websites that engage in such practices. Finally, we uncover 22 third-party entities that offer dark patterns as a turnkey solution. Based on our findings, we make recommendations for stakeholders including researchers and regulators to study, mitigate, and minimize the use of these patterns.