Dark Patterns at Scale: Findings from a Crawl of 11K Shopping Websites (1907.07032v2)

Abstract: 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.

Analysis and Implications of Dark Patterns at Scale in E-Commerce Platforms

The paper "Dark Patterns at Scale: Findings from a Crawl of 11K Shopping Websites" by Mathur et al. addresses the prevalent issue of dark patterns—deceptive design practices intended to coerce or manipulate users—across a vast number of e-commerce platforms. Through a methodical analysis involving an automated web crawler and data clustering techniques, the authors provide an empirical assessment of these practices, highlighting their widespread presence on shopping websites.

Core Findings

The investigation reveals 1,818 instances of dark patterns on 11,286 shopping websites, classifying these into 15 distinct typologies under 7 broader categories such as Sneaking, Urgency, Misdirection, and Social Proof. Notably, the paper finds that dark patterns are more often present on more popular websites, implicating a strategic deployment by companies to maximize consumer reach and influence.

Several dark patterns detected are particularly deceptive, misleading users into potentially unfavorable decisions. These include the "Sneak into Basket" tactic, where additional items are surreptitiously added to a user’s cart, and "Hidden Costs," which reveal unavoidable charges only at the last checkout step. The paper also identifies third-party services that facilitate such deceptive practices, adding another layer of complexity to their regulation and control.

Methodological Approach

The authors employ a sophisticated methodology using an automated crawler built on top of OpenWPM to simulate user interactions across 53,180 product pages. By extracting text-based elements and applying hierarchical clustering via HDBSCAN, the paper captures and classifies UI designs likely to embody dark patterns. This method not only highlights textual manipulations but also provides a scalable framework for examining user experience manipulations across the internet.

Implications for Consumer Protection

The identification of dark patterns through comprehensive web crawling and clustering represents a significant advancement toward understanding how these designs impinge upon consumer rights. The paper provides a tangible basis for discussing regulatory actions by consumer protection agencies and advocating for greater transparency and honesty in digital marketing practices. Furthermore, the presence of third-party entities promoting such patterns necessitates targeted scrutiny to curb deceptive digital marketing strategies effectively.

The paper’s findings posit a potential framework for developing countermeasures, such as browser extensions or public-awareness tools that can alert users to the presence of deceptive design elements in real-time. This proactive approach aligns with a broader regulatory goal of fostering a fairer digital marketplace.

Theoretical and Practical Prospects

The paper underscores the necessity for further research to quantitatively understand dark patterns' psychological effects on consumers. Bridging the gap between cognitive behavioral insights and HCI practices could illuminate the broader societal impacts of these manipulative designs.

From a practical perspective, the insights provided by the paper could drive the evolution of ecommerce UX toward more ethical practices, aligning with consumer interests and mitigating potential financial and data privacy risks. Moreover, the methodology and taxonomy developed could serve as a cornerstone for subsequent analyses across different platforms and regions, broadening the scope of consumer protection research.

Future Directions

The paper invites speculation on the future trajectories of AI and web development with respect to user interaction integrity. Exploring dark patterns' overlap with emerging tech ethics, in areas such as AI-driven personalization, could shape robust digital governance structures that safeguard user autonomy.

To comprehensively tackle the issue of dark patterns, interdisciplinary collaboration among legal scholars, UX designers, and cognitive psychologists is imperative. Creating a holistic framework that combines technical detection with user education and policy intervention will be key to mitigating the adverse effects of these pervasive design strategies.

In summary, Mathur et al.'s research provides a compelling foundation for ongoing discussions and interventions in digital consumer protection, emphasizing the need for continued vigilance and innovation in combating deceptive online practices.