Fake or Real? A Study of Arabic Satirical Fake News
This addresses the issue of satirical fake news being mistaken for real news on social media, particularly for Arabic language users, but is incremental as it applies existing methods to a new domain.
The study tackled the problem of identifying Arabic satirical fake news by analyzing linguistic properties and building machine learning models, achieving an accuracy of up to 98.6%.
One very common type of fake news is satire which comes in a form of a news website or an online platform that parodies reputable real news agencies to create a sarcastic version of reality. This type of fake news is often disseminated by individuals on their online platforms as it has a much stronger effect in delivering criticism than through a straightforward message. However, when the satirical text is disseminated via social media without mention of its source, it can be mistaken for real news. This study conducts several exploratory analyses to identify the linguistic properties of Arabic fake news with satirical content. We exploit these features to build a number of machine learning models capable of identifying satirical fake news with an accuracy of up to 98.6%.