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 Naïve Bayes classifier and a Support Vector Machine (SVM). The considered features range from single words to n-grams 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.
KeywordsSupport Vector Machine Natural Language Processing Machine Translation Polynomial Kernel Sentence Length
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