Autores
Arif Muhammad
Tonja Atnafu Lambebo
Ameer Iqra
Kolesnikova Olga
Gelbukh Alexander
Sidorov Grigori
Meque Abdul Gafar Manuel
Título CIC at CheckThat! 2022: Multi-class and Cross-lingual Fake News Detection
Tipo Congreso
Sub-tipo Memoria
Descripción 2022 Conference and Labs of the Evaluation Forum, CLEF 2022
Resumen Nowadays, social media is one widely used platform to access information. Fake news on social media and various other media is widely spreading. It is a matter of serious concern due to its ability to cause a lot of social and national damage with destructive impacts. Therefore, detecting misleading news is critical to detect automatically. Fake news detection software has been used in a variety of fields, such as social media, health, political news, etc. This paper presents the Instituto Politécnico Nacional (Mexico) at CheckThat! 2022. In this paper, we discuss using different algorithms for the multiclass and cross-lingual fake news detection task. We achieved a macro F1-score of 28.60% for a mono-lingual task in English (task 3a) using RoBERTa pre-trained model and 17.21% for a cross-lingual task for English and German (task 3b) using Bi-LSTM deep learning algorithm. © 2022 Copyright for this paper by its authors.
Observaciones CEUR Workshop Proceedings, v. 3180
Lugar Bologna
País Italia
No. de páginas 434-443
Vol. / Cap.
Inicio 2022-09-05
Fin 2022-09-08
ISBN/ISSN