UNIBA - Integrating distributional semantics features in a supervised approach for detecting irony in Italian tweets
Pierpaolo Basile, Giovanni Maria Semeraro · Accademia University Press eBooks · 2018
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, micro-blogging 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.