TuPy-E: detecting hate speech in Brazilian Portuguese social media with
  a novel dataset and comprehensive analysis of models
Felipe Oliveira Victoria Reis Nelson Ebecken
Social media has become integral to human interaction, providing a platform
for communication and expression. However, the rise of hate speech on these
platforms poses significant risks to individuals and communities. Detecting and
addressing hate speech is particularly challenging in languages like Portuguese
due to its rich vocabulary, complex grammar, and regional variations. To
address this, we introduce TuPy-E, the largest annotated Portuguese corpus for
hate speech detection. TuPy-E leverages an open-source approach, fostering
collaboration within the research community. We conduct a detailed analysis
using advanced techniques like BERT models, contributing to both academic
understanding and practical applications