URJC-Team at HOPE2023@IberLEF: Multilingual Hope Speech Detection Using Transformers Architecture

  • Miguel Ángel Rodríguez-García*
  • , Adrián Riaño-Martínez
  • , Soto Montalvo Herranz
  • *Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

Abstract

Detecting Hope Speech refers to identifying content in natural language that provokes optimism in people's minds, encouraging them to improve their life. This type of speech has a relevant target in our society, offering supporting messages for people suffering from depression, stress and loneliness. Despite its relevance, a significant number of published studies address to recognise the flip side of the coin, hate speech. This work describes our contribution to the HOPE challenge, i.e., detecting hope speech content in Spanish and English texts. Two different transform models are proposed to tackle the subtasks suggested in the challenge. Our proposal reaches notable results.

Original languageEnglish
JournalCEUR Workshop Proceedings
Volume3496
DOIs
Publication statusPublished - 2023
Externally publishedYes
Event2023 Iberian Languages Evaluation Forum, IberLEF 2023 - Jaen, Spain
Duration: 26 Sept 2023 → …

Keywords

  • Deep Learning
  • Hope Speech
  • Natural Language Processing
  • Transformers

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