Understanding User and Developer Perceptions of Dark Patterns in Online Environments

With the rapid development of technology, software applications have become essential in people's daily lives. The number of digital platforms (e.g., website and mobile) available is continuously growing, and so are the persuasive designs that impact user's experience and decision-making in an online environment. Deceptive patterns, also known as dark patterns, refer to user interface (UI) design choices crafted to manipulate or trick users into actions that they are not intended to do in digital environments. These patterns, found everywhere in digital interfaces, exploit users' psychological vulnerability and manipulate them into actions that benefit stakeholders at the expense of users' interests. To bring more awareness of the dark patterns, scholarship on the topic is vastly increasing. However, there is limited study on how dark patterns impact users' perceptions and interaction with applications. Furthermore, work has yet to investigate dark patterns from the perspective of software engineers, the developers who implement user interface designs. To that end, our study seeks to explore users' and developers' perspectives on dark patterns In this study, we used a mixed-method approach, surveying each stakeholder group (N_user=66 and N_developer=38) and mining GitHub data (N=2556) to understand end users' perceptions and experiences and developers' discussions and attitudes about dark patterns. Our findings reveal that users often encounter dark patterns online with limited options for avoidance, which evoke negative emotions. Developers report that external pressures influence their decisions to implement dark patterns, and most recognize their adverse effects on trust and user experience. Discussions on GitHub primarily focus on the existence and prevention of dark patterns, often reflecting negative sentiments. With our findings, we aim to raise stakeholders' awareness of dark patterns and promote ethical UI design to mitigate the use of deceptive designs in online environments.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

Computer Science & Applications

Department dc:contributor.department

Computer Science and#38; Applications

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2025

Author dc:creator

• Liang, Huayu

Chair dc:contributor.committeechair

• Brown, Dwayne Christian

Committee members dc:contributor.committeemember

• Dunlap, Daniel
• Lee, Sang Won

• Dark Patterns
• Deceptive Design
• Empirical Study
• Sentiment Analysis

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Language dc:language.iso

en

Dc Identifier Other

vt_gsexam:42480

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/123900