CLAILGNov 18, 2022

Overview of the WANLP 2022 Shared Task on Propaganda Detection in Arabic

arXiv:2211.10057v1302 citationsh-index: 47
Originality Synthesis-oriented
AI Analysis

This work addresses the language gap in propaganda detection research, focusing on Arabic social media, but it is incremental as it extends existing methods to a new language.

The paper tackled the problem of propaganda detection in Arabic tweets by organizing a shared task with two subtasks: multilabel classification and span detection, attracting 63 team registrations and submissions from 14 and 3 teams respectively.

Propaganda is the expression of an opinion or an action by an individual or a group deliberately designed to influence the opinions or the actions of other individuals or groups with reference to predetermined ends, which is achieved by means of well-defined rhetorical and psychological devices. Propaganda techniques are commonly used in social media to manipulate or to mislead users. Thus, there has been a lot of recent research on automatic detection of propaganda techniques in text as well as in memes. However, so far the focus has been primarily on English. With the aim to bridge this language gap, we ran a shared task on detecting propaganda techniques in Arabic tweets as part of the WANLP 2022 workshop, which included two subtasks. Subtask~1 asks to identify the set of propaganda techniques used in a tweet, which is a multilabel classification problem, while Subtask~2 asks to detect the propaganda techniques used in a tweet together with the exact span(s) of text in which each propaganda technique appears. The task attracted 63 team registrations, and eventually 14 and 3 teams made submissions for subtask 1 and 2, respectively. Finally, 11 teams submitted system description papers.

Foundations

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