11 mai 2021
https://creativecommons.org/licenses/by-nc-nd/4.0/ , info:eu-repo/semantics/openAccess
Maurizio Moraca et al., « UninaStudents @ SardiStance: Stance Detection in Italian Tweets - Task A », Accademia University Press, ID : 10.4000/books.aaccademia.7189
This document describes a classification system for the SardiStance task at EVALITA 2020. The task consists in classifying the stance of the author of a series of tweets towards a specific discussion topic. The resulting system was specifically developed by the authors as final project for the Natural Language Processing class of the Master in Computer Science at University of Naples Federico II. The proposed system is based on an SVM classifier with a radial basis function as kernel making use of features like 2 char-grams, unigram hashtag and Afinn weight computed on automatic translated tweets. The results are promising in that the system performances are on average higher than that of the baseline proposed by the task organizers.