Problem
Research questions and friction points this paper is trying to address.
Analyzing dark patterns in user journeys
Developing temporal analysis methodology
Exploring combinatorial effects of dark patterns
Getting Trapped in Amazon's"Iliad Flow": A Foundation for the Temporal Analysis of Dark Patterns
🤖 AI Summary
This paper addresses the challenge of dark patterns that dynamically combine and evolve across user journeys to manipulate behavior over time. Method: We propose Temporal Analysis of Dark Patterns (TADP), the first systematic methodology for temporal dark pattern analysis, instantiated through the Amazon Prime “Iliad Flow” case study. Our approach integrates regulatory complaint text mining, user journey modeling, and dark pattern ontology mapping to characterize both single- and multi-pattern temporal evolution and combinatorial effects. Contribution/Results: TADP advances beyond traditional static and isolated analyses by identifying critical temporal anchor points and pattern-combination signatures. It supports expert forensic analysis and enables the design of automated detection pipelines. Furthermore, it establishes a scalable, temporally grounded analytical framework for regulatory intervention and platform compliance assessment—offering a novel paradigm for evaluating manipulative interface practices in longitudinal contexts.
📝 Abstract
Dark patterns are ubiquitous in digital systems, impacting users throughout their journeys on many popular apps and websites. While substantial efforts from the research community in the last five years have led to consolidated taxonomies of dark patterns, including an emerging ontology, most applications of these descriptors have been focused on analysis of static images or as isolated pattern types. In this paper, we present a case study of Amazon Prime's"Iliad Flow"to illustrate the interplay of dark patterns across a user journey, grounded in insights from a US Federal Trade Commission complaint against the company. We use this case study to lay the groundwork for a methodology of Temporal Analysis of Dark Patterns (TADP), including considerations for characterization of individual dark patterns across a user journey, combinatorial effects of multiple dark patterns types, and implications for expert detection and automated detection.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Temporal Analysis of Dark Patterns
Characterization across user journey
Combinatorial effects of patterns
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