Abstract
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.
Cite
CITATION STYLE
Santilli, A., Croce, D., & Basili, R. (2018). A kernel-based approach for irony and sarcasm detection in Italian. In CEUR Workshop Proceedings. CEUR-WS. https://doi.org/10.4000/books.aaccademia.4613
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