UrduFake@FIRE2021: Shared Track on Fake News Identification in Urdu

Maaz Amjad, Sabur Butt, Hamza Imam Amjad, Alisa Zhila, Grigori Sidorov, Alexander Gelbukh

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

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.

Idioma originalInglés
Título de la publicación alojadaFIRE 2021 - Proceedings of the 13th Annual Meeting of the Forum for Information Retrieval Evaluation
EditoresDebasis Ganguly, Surupendu Gangopadhyay, Mandar Mitra, Prasenjit Majumder, Prasenjit Majumder
EditorialAssociation for Computing Machinery
Páginas19-21
Número de páginas3
ISBN (versión digital)9781450395960
DOI
EstadoPublicada - 13 dic. 2021
Evento13th Annual Meeting of the Forum for Information Retrieval Evaluation, FIRE 2021 - Virtual, Online, India
Duración: 13 dic. 202117 dic. 2021

Serie de la publicación

NombreACM International Conference Proceeding Series

Conferencia

Conferencia13th Annual Meeting of the Forum for Information Retrieval Evaluation, FIRE 2021
País/TerritorioIndia
CiudadVirtual, Online
Período13/12/2117/12/21

Huella

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