This study addresses the scarcity of research on cyberbullying in Latin America and the Caribbean (LAC) due to the region's linguistic complexity. Therefore, it focuses on comparing four machine learning models to detect cyberbullying on Twitter, emphasizing Peruvian Spanish. It uses a dataset specifically designed for training the models and presents detailed results on their performance. By highlighting the effectiveness of these models, the study aims to foster further interest in cyberbullying research in LAC, providing a basis for future studies and intervention strategies in the region.
