STUFIIT at SemEval-2019 Task 5: Multilingual Hate Speech Detection on Twitter with MUSE and ELMo Embeddings
Michal Bojkovský, Matúš Pikuliak · 2019
We evaluate the viability of multilingual learning for the task of hate speech detection.We also experiment with adversarial learning as a means of creating a multilingual model.Ultimately our multilingual models have had worse results than their monolignual counterparts.We find that the choice of word representations (word embeddings) is very crucial for deep learning as a simple switch between MUSE and ELMo embeddings has shown a 3-4% increase in accuracy.This also shows the importance of context when dealing with online content.