Integrating Dark Pattern Taxonomies
Frank Lewis, Julita Vassileva
TL;DR
The paper addresses the lack of a unified labeling system for Dark Patterns in UI/UX and proposes a graph-based integration of existing taxonomies, anchored on Ahuja et al. (2022), with community detection to reveal cross-domain pattern groups. It identifies 10 DP communities centered on four core themes, notably Information Hiding, and argues that this integrated taxonomy can underpin a Globally Harmonized System for dark patterns and glyph-based hazard communication. The approach aims to aid regulation, consumer education, and cross-domain accountability by providing a scalable, domain-agnostic framework. This work provides a methodological starting point for standardizing dark pattern taxonomy and informing regulators and designers about common patterns and their interrelations.
Abstract
The problem of ``Dark Patterns" in user interface/user experience (UI/UX) design has proven a difficult issue to tackle. Malicious and explotitative design has expanded to multiple domains in the past 10 years and which has in turn led to multiple taxonomies attempting to describe them. While these taxonomies holds their own merit, and constitute unique contributions to the literature, their usefulness as separate entities is limited. We believe that in order to make meaningful progress in regulating malicious interface design, we must first form a globally harmonized system (GHS) for the classification and labeling of Dark Patterns. By leaning on network analysis tools and methods, this paper synthesizes existing taxonomies and their elements through as a directed graph. In doing so, the interconnectedness of Dark patterns can be more clearly revealed via community (cluster) detection. Ultimately, we hope that this work can serve as the inspiration for the creation of a glyph-based GHS for the classification of Dark Patterns.