Some Experiments in Humour Recognition Using the Italian Wikiquote Collection

In this paper we present some results obtained in humour classification over a corpus of Italian quotations manually extracted and tagged from the Wikiquote project. The experiments were carried out using both a multinomial Na¨ıve Bayes classifier and a Support Vector Machine (SVM). The considered features range from single words to ngrams and sentence length. The obtained results show that it is possible to identify the funny quotes even with the simplest features (bag of words); the bayesian classifier performed better than the SVM. However, the size of the corpus size is too small to support definitive assertions.

• Type: Conference
• Year: 2007
• Where: WILF
• Authors: Davide Buscaldi, Paolo Rosso
• Keywords: Artificial Intelligence, Corpus Size, Multinomial Na¨ıve Bayes, Support Vector Machine, WILF 2007