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Staring Into the Darkness: The Heuristic Evaluation of Manipulative Interfaces.

Date

2025-05-29

Journal Title

Journal ISSN

Volume Title

Publisher

ORCID

0000-0001-6929-4455

Type

Thesis

Degree Level

Masters

Abstract

Dark Patterns (DPs) are the foundation of what has come to be called ``Deceptive Design'' and represent a significant issue in the world of user interface and user experience design. By exploiting user cognition through interface design, DPs cause users to forfeit their resources (i.e., time, money, data) for the benefit of the interface designer. As a ubiquitous phenomenon, numerous taxonomies and ontologies from various domains have been proposed to classify DPs and fragmented our understanding of them. This fragmentation complicates legislative efforts as well as knowledge-sharing between the domains they appear in. To address limitations surrounding the fragmentation, extensibility, and comprehensibility of contemporary DP ontologies and taxonomies, this thesis proposes a new method of DP identification and classification based on heuristic evaluation. By condensing the past decade of DP taxonomies via network analysis and distilling/contextualizing the result with Straussian grounded theory, we have created a set of five heuristics to evaluate potentially manipulative elements in user interfaces. Our work describes the construction of our heuristics and reports on their use in an evaluation conducted by human computer interaction researchers at the University of Saskatchewan. The results suggest that our heuristics and the heuristic evaluation process can improve DP detection and delineate manipulative from benign design choices. As a naturally inexpensive, approachable, and versatile evaluation method that provides rich and accessible qualitative data, we propose heuristic evaluation as a valuable addition to the evaluation of manipulative interfaces.

Description

Keywords

Heuristic evaluation, Dark Patterns, Online Manipulation, Interface Design, Computer Science, HCI

Citation

Degree

Master of Science (M.Sc.)

Department

Computer Science

Program

Computer Science

Advisor

Part Of

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DOI

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