When humour hurts: linguistic features to foster explainability

Resumen

The main objective of this research is to use different features for the textual representation of humorous texts and detect which are the characteristics that distinguish non-offensive jokes from the highly offensive ones. For this purpose, we use the data from the HaHackaton task in which jokes are annotated according to their degree of offensiveness. A new classification task is created by using two subsets of the jokes: the non-offensive ones and the highly offensive ones.The features with statistically significant differences in the two groups are used. By applying an ablation test, the most relevant features are used for a second classification task, showing that it is possible to obtain the same results with fewer computational resources.