@inproceedings{vallecillo-rodrguez-etal-2023-sinai,
    title = "{SINAI} at {S}em{E}val-2023 Task 10: Leveraging Emotions, Sentiments, and Irony Knowledge for Explainable Detection of Online Sexism",
    author = "Vallecillo Rodrguez, Mar{\'\i}a Estrella  and
      Plaza Del Arco, Flor Miriam  and
      Ure{\~n}a L{\'o}pez, L. Alfonso  and
      Mart{\'\i}n Valdivia, M. Teresa",
    editor = {Ojha, Atul Kr.  and
      Do{\u{g}}ru{\"o}z, A. Seza  and
      Da San Martino, Giovanni  and
      Tayyar Madabushi, Harish  and
      Kumar, Ritesh  and
      Sartori, Elisa},
    booktitle = "Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)",
    month = jul,
    year = "2023",
    address = "Toronto, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.semeval-1.136",
    doi = "10.18653/v1/2023.semeval-1.136",
    pages = "986--994",
    abstract = "This paper describes the participation of SINAI research team in the Explainable Detection of Online Sexism (EDOS) Shared Task at SemEval 2023. Specifically, we participate in subtask A (binary sexism detection), subtask B (category of sexism), and subtask C (fine-grained vector of sexism). For the three subtasks, we propose a system that integrates information related to emotions, sentiments, and irony in order to check whether these features help detect sexism content. Our team ranked 46th in subtask A, 37th in subtask B, and 29th in subtask C, achieving 0.8245, 0.6043, and 0.4376 of macro f1-score, respectively, among the participants.",
}

This paper describes the participation of SINAI research team in the Explainable Detection of Online Sexism (EDOS) Shared Task at SemEval 2023. Specifically, we participate in subtask A (binary sexism detection), subtask B (category of sexism), and subtask C (fine-grained vector of sexism). For the three subtasks, we propose a system that integrates information related to emotions, sentiments, and irony in order to check whether these features help detect sexism content. Our team ranked 46th in subtask A, 37th in subtask B, and 29th in subtask C, achieving 0.8245, 0.6043, and 0.4376 of macro f1-score, respectively, among the participants.
Vallecillo Rodrguez, Mar{\'\i}a Estrella Plaza Del Arco, Flor Miriam Ure{\~n}a L{\'o}pez, L. Alfonso Mart{\'\i}n Valdivia, M. Teresa
SINAI at SemEval-2023 Task 10: Leveraging Emotions, Sentiments, and Irony Knowledge for Explainable Detection of Online Sexism