Pythoneers at WANLP 2022 Shared Task: Monolingual AraBERT for Arabic Propaganda Detection and Span Extraction
Year: 2022
Type: conference-paper
Abstract: In this paper, we present two deep learning approaches that are based on AraBERT, submitted to the Propaganda Detection shared task of the Seventh Workshop for Arabic Natural Language Processing (WANLP 2022).Propaganda detection consists of two main sub-tasks, mainly propaganda identification and span extraction.We present one system per sub-task.The first system is a Multi-Task Learning model that consists of a shared AraBERT encoder with task-specific binary classification layers.This model is trained to jointly learn one binary classification task per propaganda method.The second system is an AraBERT model with a Conditional Random Fields (CRF) layer.We achieved rank 3 on the first sub-task and rank 1 on the second sub-task.
Authors: Joseph Attieh, Fadi Hassan
Institution: Aalto University
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4385574492