  Most hate speech detection research focuses on a single language, generally
English, which limits their generalisability to other languages. In this paper
we investigate the cross-lingual hate speech detection task, tackling the
problem by adapting the hate speech resources from one language to another. We
propose a cross-lingual capsule network learning model coupled with extra
domain-specific lexical semantics for hate speech (CCNL-Ex). Our model achieves
state-of-the-art performance on benchmark datasets from AMI@Evalita2018 and
AMI@Ibereval2018 involving three languages: English, Spanish and Italian,
outperforming state-of-the-art baselines on all six language pairs.
