Dark Patterns at Scale

By Arunesh Mathur, Gunes Acar, Michael Friedman, Elena Lucherini, Jonathan R. Mayer, M. Chetty, Arvind Narayanan. Proc. ACM Hum. Comput. Interact., 2019

417 citations recorded by the source corpus.

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 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 1,818 dark pattern instances, together representing 15 types and 7 broader categories. We examine these dark patterns for deceptive practices, and find 183 websites that engage in such practices. We also uncover 22 third-party entities that offer dark patterns as a turnkey solution. Finally, we develop a taxonomy of dark pattern characteristics that describes the underlying influence of the dark patterns and their potential harm on user decision-making. Based on our findings, we make recommendations for stakeholders including researchers and regulators to study, mitigate, and minimize the use of these patterns.

Subfields: Information Systems, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/8cc5711098f32f48dbd7a123cc4d8723c3d64238

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Information Systems

1. Thorsten Holz
2. Lalana Kagal
3. David R Karger
4. Michael Veale
5. Florian Schaub

In Sociology and Political Science

1. Michael Veale
2. Florian Schaub

Citations in the corpus

• (Un)informed Consent: Studying GDPR Consent Notices in the Field (2019, background): “xamples include color [40] and position [9]. Studies investigating different notice designs were conducted, for example, for SSL [16], browser security [33], and phishing warnings [13]. Mathur et al. [28] classified commondark patterns in web services. In their classification scheme the observed act”
• Dark Patterns after the GDPR: Scraping Consent Pop-ups and Demonstrating their Influence (2020, background): “The practice of dark patterns for privacy notices — while only sometimes discussed under this moniker in HCI and privacy literature [9, 15, 29, 38] — is extensively reported on by consumer protection organisations [28], white papers [49], and popular press [47] (for an excellent overview, see the No”