Autores
Krasitskii Mikhail
Kolesnikova Olga
Sidorov Grigori
Gelbukh Alexander
Título HOPE2024@IberLEF: A Cross-Linguistic Exploration of Hope Speech Detection in Social Media
Tipo Congreso
Sub-tipo Memoria
Descripción 6th Iberian Languages Evaluation Forum, IberLEF 2024
Resumen Hope includes the belief and expectations that we have for the realization of desired events. It is a hopeful prospect or expectation that positive circumstances will unfold or conditions will improve. These emotions are a core human emotion and mindset that drives people to persevere in the face of obstacles, pursue their ambitions, and believe in the potential for better outcomes even in the midst of challenges. Through attention to binary classification in hope research, we can categorize hopeful states as either "Hope" or "Not Hope." Additionally, the "Hope" classification is segmented into three specific types: "Generalized Hope," "Realistic Hope," and "Unrealistic Hope. Our impressive outcomes, driven by analysis and training data, were achieved through transformer methods showcased in the HOPE track of the IberLEF 2024 competition. Our proposed method achieved very competitive results in all subtasks, however, the best-performing result secured an average macro F1 score of 0.85 in the binary hope speech detection subtask in the English language. © 2024 Copyright for this paper by its authors.
Observaciones CEUR Workshop Proceedings, v. 3756
Lugar Valladolid
País España
No. de páginas
Vol. / Cap.
Inicio 2024-09-24
Fin
ISBN/ISSN