They also highlighted the fact that different features are important for each hate-speech label, all of which cannot be captured by a single model.
ensemble methods have been used by studies such as Park and Fung (2017), who have used a hybrid-Convolutional Neural Network (CNN) which combines word and character level CNN, Pitsilis et al. (2018), who have used an ensemble of Long Short-term Memory (LSTM) classifiers with majority voting and confidence based aggregation, and Mahata et al. (2019), who used an ensemble of CNN and LSTM based classifiers to capture both salient local information and long term contexts