CHILab at HaSpeeDe3: Overview of the Taks A Textual

Abstract

This technical report illustrates the system developed by the CHILab team for the competition HaSpeeDe3 as part of the EVALITA 2023 campaign. The key idea for HaSpeeDe3 task A - Political Hate Speech Detection - Textual, was to develop different systems arranged as suitable combinations of the Pre-Trained Language Model (PTLM) used for embedding extraction, neural architectures for further elaborations over the embeddings and a classifier. In particular, dense layers, LSTM, BiLSTM and Transformers were used. The best performing system across the ones investigated in this report was made by embeddings extracted via XLM-RoBERTa coupled with BiLSTM that reaches a macro-F1 score of 0.876.