| Título |
DSVS at PAN 2024: Ensemble Approach of Transformer-based Language Models for Analyzing Conspiracy Theories Against Critical Thinking Narratives |
| Tipo |
Revista |
| Sub-tipo |
JCR |
| Descripción |
25th Working Notes of the Conference and Labs of the Evaluation Forum, CLEF 2024 |
| Resumen |
This paper presents a comprehensive analysis of ensemble models for the shared task "Conspiracy Theories Against Critical Thinking Narratives" for PAN at CLEF 2024. Through a data collection involving Telegram conversations on COVID-19, two distinct corpora in English and Spanish were assembled and manually labeled to differentiate between "critical" and "conspiracy" texts. The study employed ensemble models, comprising seven trained transformer-based models per language-task pair, to address two key tasks: distinguishing between critical and conspiracy texts (binary classification) and detecting spans for six different categories that can be found on the texts (multi-label span classification). The results unveiled the competitive performance of ensemble models, particularly in securing notable rankings surpassing the mean of all participants' results in both tasks. © 2024 Copyright for this paper by its authors. |
| Observaciones |
CEUR Workshop Proceedings, v. 3740 |
| Lugar |
Grenoble |
| País |
Francia |
| No. de páginas |
2554-2565 |
| Vol. / Cap. |
|
| Inicio |
2024-09-09 |
| Fin |
2024-09-12 |
| ISBN/ISSN |
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