GolpeBR: Construction and Validation of an Annotated Dataset on Banking Scams and Fraud - Souza, Tamyres Vial de; Tirloni, Jhonata; Belo, Felipe; Araujo, Nelcileno Virgilio; Ventura, Thiago M.; Oliveira, Allan Gonçalves de (Anais do Simpósio Brasileiro de Tecnologia da Informação e da Linguagem Humana (STIL); 2025: Anais do XVI Simpósio Brasileiro de Tecnologia da Informação e da Linguagem HumanaDO - 10.5753/stil.2025.37844, 2025)
This article details the construction and validation of the GolpeBR dataset, which was created from news articles and Reddit posts. Automated Python methods were used to extract and process the data, which was then annotated using the Deepseek-R1 LLM and the 5W1H methodology. A cybersecurity expert classified and validated the records, distinguishing between banking cybercrimes and unrelated crimes. For the dataset's validation, supervised learning algorithms were applied. It was found that models trained with data structured by the 5W1H methodology demonstrated better accuracy, reaching 0.83 for the Logistic Regression and Random Forest algorithms.