Year: 2022
Type: conference-paper
Abstract: Nowadays, the rapid dissemination of data on digital platforms has resulted in the emergence of information pollution and data contamination, specifically misinformation, mal-information, disinformation, fake news, and various types of propaganda.These topics are now posing a serious threat to the online digital realm, posing numerous challenges to social media platforms and governments around the world.In this article, we propose a propaganda detection model based on the transformer-based model AraBERT, with the objective of using this framework to detect propagandistic content in the Arabic social media text scene, with purpose of making online Arabic news and media consumption healthier and safer.Given the dataset, our results are relatively encouraging, indicating a huge potential for this line of approaches in Arabic online news text NLP.
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4385573180