Cervical cancer is a significant global health issue, and understanding the characteristics associated with this disease can contribute to its early detection and prevention. In this study, we conducted a data mining analysis on a dataset obtained from ‘Hospital Universitario de Caracas’, consisting of demographic information, habits, and medical records of 858 patients. Using machine learning techniques, we identified social characteristics of the dataset related to cervical screening, including age, number of sexual partners, and history of sexually transmitted diseases. While the dataset content may not be directly correlated with cervical cancer in social factors dimensions, we can gain insights into the impact on common sexually transmitted diseases.