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PREDICTING RESPONSE TO DARK PATTERNS BASED ON INDIVIDUAL DIFFERENCES

thesis
posted on 2023-06-06, 19:41 authored by Sneha Lekha UppalaSneha Lekha Uppala

With the advent of the Internet, the digital market saw growth in online businesses, and now, it is impossible to imagine a world without the Internet. The prevalence of online services increased the internet user base, and employing different UX designs attracted more customers. With increased competition, profits, and growth in mind, businesses started using various dark design pattern strategies to seek data, profits, and attention. Dark patterns are user interface design techniques that manipulate user behavior in deceptive ways, often leading to unintended outcomes. As the use of these patterns continues to grow, it is crucial to understand how users respond to them based on their Individual differences. Earlier research revealed how effective these dark pattern strategies are, how prevalent they are, and how users perceive and feel about them. However, there needs to be more research on how users respond to these dark pattern strategies based on individual differences. The research aims to understand what individual differences predict their responses to different types of dark patterns. 

The study recruited participants through Amazon Mechanical Turk (MTurk), a widely used online marketplace for paid tasks. The survey consisted of several questionnaires, including demographic information, individual differences (such as the Big Five personality traits, impulsivity, and internet addiction), and vignettes containing dark patterns. 

Data was collected from 259 participants and imported into SPSS for analysis. The correlational analysis identified statistically significant variables related to dark pattern strategies. The results indicated that extroversion and agreeableness were significant predictors of dark pattern compliance. Specifically, individuals who scored higher in extroversion and lower in agreeableness were more likely to comply with the dark patterns presented in the vignettes. These findings have important implications for designers, policymakers, and consumers. Designers should consider individual differences when designing user interfaces to avoid using manipulative techniques that could lead to unintended outcomes. Policymakers should consider regulating the use of dark patterns to protect consumers from potentially harmful practices. Consumers should be aware of the dark patterns and how they may affect their behavior, making informed decisions when interacting with online platforms. 

The results of this study also contribute to the growing body of literature on individual differences and their relationship to user behavior. Previous studies revealed that personality traits, cognitive styles, and other individual differences can influence how users interact with technology. This study expands on this research by explicitly investigating the role of Big Five personality traits, impulsivity, and internet addiction in predicting user responses to dark patterns. In conclusion, this research paper contributes to understanding how individual differences can predict user responses to dark patterns. The study highlights the importance of considering individual differences when designing user interfaces to avoid using manipulative techniques. 

History

Degree Type

  • Master of Science

Department

  • Computer and Information Technology

Campus location

  • West Lafayette

Advisor/Supervisor/Committee Chair

Kathryn C. Seigfried-Spellar

Additional Committee Member 2

Paul Parsons

Additional Committee Member 3

Tianyi Li