AraBEM at WANLP 2022 Shared Task: Propaganda Detection in Arabic Tweets

Abstract

Propaganda is information or ideas that an organised group or government spreads to influence peoples' opinions, especially by not giving all the facts or secretly emphasising only one way of looking at the points. The ability to automatically detect propaganda-related language is a challenging task that researchers in the NLP community have recently started to address. This paper presents the participation of our team AraBEM in the propaganda detection shared task on Arabic tweets. Our system utilised a pre-trained BERT model to perform multi-class binary classification. It attained the best score at 0.602 micro-f1, ranking third on subtask-1, which identifies the propaganda techniques as a multilabel classification problem with a baseline of 0.079.