@conference{araque2023emit,
author = "Araque, Oscar and Simona Frenda and Rachele Sprugnoli and Debora Nozza and Viviana Patti",
abstract = "The Emotions in Italian (EMit) task is the first edition of a shared task on emotion analysis and opinion mining in Italian messages at EVALITA 2023. EMit presents two subtasks: (i) Subtask A, that consists in an emotion detection challenge, and (ii) Subtask B, that introduces a novel problem of target detection of the expressed emotion. Additionally, EMit challenges systems with a thorough in-domain and out-of-domain evaluation, probing the generalization capabilities of the submitted solutions. In general, 4 teams have participated in Subtask A, achieving a macro-averaged f-score of 0.6028 and 0.4977 in the in-domain and out-of-domain sets, respectively. In Subtask B a team has participated, obtaining 0.6459 in the in-domain set and 0.3223 in the out-of-domain set as macro-averaged f-scores. The obtained results indicate that further work needs to be done to solve the task, opening new avenues of research.",
booktitle = " Eighth Evaluation Campaign of Natural Language Processing and Speech Tools for Italian",
editor = "CEUR",
issn = "1613-0073",
keywords = "natural language processing;emotion analysis;machine learning",
number = "3473",
title = " {EM}it at {EVALITA} 2023: {O}verview of the {C}ategorical {E}motion {D}etection in {I}talian {S}ocial {M}edia {T}ask",
url = "https://ceur-ws.org/Vol-3473/paper1.pdf",
volume = "3473",
year = "2023",
}