A Kernel-based Approach for Irony and Sarcasm Detection in Italian


This paper describes the UNITOR system that participated to the Irony Detection in Italian Tweets task (IronITA) within the context of EvalIta 2018. The system corresponds to a cascade of Support Vector Machine classifiers. Specific features and kernel functions have been proposed to tackle the different subtasks: Irony Classification and Sarcasm Classification. The proposed system ranked first in the Sarcasm Detection subtask (out of 7 submissions), while it ranked sixth (out of 17 submissions) in the Irony Detection task

Proceedings of the 6th evaluation campaign of Natural Language Processing and Speech tools for Italia
Andrea Santilli
Andrea Santilli
PhD Student in Computer Science

PhD Student passionate about natural language processing, representation learning and machine intelligence.