Autores
Amjad - Maaz
Butt Sabur
Sidorov Grigori
Gelbukh Alexander
Título UrduFake@FIRE2021: Shared Track on Fake News Identification in Urdu
Tipo Congreso
Sub-tipo Indefinido
Descripción 13th Annual Meeting of the Forum for Information Retrieval Evaluation, FIRE 2021
Resumen This study reports the second shared task named as UrduFake@Fire2021 on identifying fake news detection in Urdu language. This is a binary classification problem in which the task is to classify a given news article into two classes: (i) real news, or (ii) fake news. In this shared task, 34 teams from 7 different countries (China, Egypt, Israel, India, Mexico, Pakistan, and UAE)registered to participate in the shared task, 18 teams submitted their experimental results and 11 teams submitted their technical reports. The proposed systems were based on various count-based features and used different classifiers as well as neural network architectures. The stochastic gradient descent (SGD) algorithm outperformed other classifiers and achieved 0.679 F-score. © 2021 Owner/Author.
Observaciones DOI 10.1145/3503162.3505240
Lugar Virtual, online
País Indefinido
No. de páginas 9-21
Vol. / Cap.
Inicio 2021-12-13
Fin 2021-12-17
ISBN/ISSN 9781450395960