Resumo (PT):
Abstract (EN):
This paper summarizes the participation of
Stop PropagHate team at SemEval 2019. Our
approach is based on replicating one of the
most relevant works on the literature, using
word embeddings and LSTM. After circumventing some of the problems of the original
code, we found poor results when applying it
to the HatEval contest (F1=0.45). We think
this is due mainly to inconsistencies in the data
of this contest. Finally, for the OffensEval the
classifier performed well (F1=0.74), proving
to have a better performance for offense detection than for hate speech.
Language:
English
Type (Professor's evaluation):
Scientific
No. of pages:
8