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English. This paper describes the UNIBA team participation in the IronITA 2018 task at EVALITA 2018. We propose a supervised approach based on LIBLINEAR that relies on keyword, polarity, microblogging features and representation of tweets in a distributional semantic model. Our system ranked 3rd and 4th in the irony detection subtask. We participated only in the constraint run exploiting the training data provided by the task organizers. Italiano. Questo articolo descrive la partecipazione del team UNIBA al task IronITA 2018 organizzato durante EVALITA 2018. Nell’articolo proponiamo un approccio supervisionato basato su LIBLINEAR che sfrutta le parole chiave, la polarità, attributi tipici dei microblog e la rappresentazione dei tweet in uno spazio semantico distribuzionale. Il nostro sistema si è classificato terzo e quarto nel sotto task di identificazione dell’ironia. Abbiamo partecipato solamente nel constraing run utilizzando i dati di training forniti dagli organizzatori del task.

UNIBA - Integrating distributional semantics features in a supervised approach for detecting irony in Italian tweets