| Resumen |
The process of identifying hope speech involves classifying sentences into those that convey hopeful messages and those that do not, based on a dataset of text data. Hopeful expression encompasses positive, supportive, inclusive, and reassuring communications aimed at inspiring optimism in individuals. Unlike the focus on recognizing and reducing negative language usage, detecting hope speech aims to discover and enhance positive modes of communication in online interactions. In our paper, we detail our participation in the HOPE: Multilingual Hope Speech Detection shared task at IberLEF 2024. This task includes two sub-tasks: identifying hope speech in Spanish and English tweets sourced from social media content. Our approach with BERT multilingual employs a word-based tokenization strategy for training which yielded an F1 Score of 0.71 for Spanish and 0.74 for English language. © 2024 Copyright for this paper by its authors. |
