Detecção e análise de dark patterns em plataformas de apostas no Brasil

Abstract

The rapid expansion of sports betting platforms in Brazil has brought about the prolifera- tion of manipulative design techniques, known as Dark Patterns, which can compromise

user autonomy and decision-making. This dissertation proposes a hybrid methodology for the identification and analysis of these practices, integrating Natural Language Processing (NLP) techniques and structural interface inspection. The methodological path involved the investigation of 22 platforms operating in the national market during the period in which the research was conducted. For textual analysis, the BERTimbau model — a Transformer-based architecture fine-tuned for Brazilian Portuguese — was used, achieving a weighted average F1-Score of 0.82 in the classification of categories such as Urgency and Social Proof. Concurrently, the inspection of style sheets (CSS) revealed more than 8,000 occurrences of the opacity:0 property, signaling the presence of potentially hidden or obstructive interface elements. The results show that platforms adapt traditional e-commerce tactics to the betting context, exploring cognitive vulnerabilities through

temporal pressure and programmed technical barriers. It is concluded that the sophisti- cation of these strategies, although detectable by automated methods, demands specific

regulation regarding interface design in the sector, aiming for consumer protection and the preservation of mental health in the face of predatory business models.