An Evaluation of the Automatic Detection of Hate Speech in Social Media Networks

Numerous approaches have been developed over recent years to detect hate speech on social media networks. Nevertheless, a great deal of what is generally recognized as cannot yet be detected. There remain many challenges assuring the effectiveness and reliability automatic detection systems in different languages, including Arabic. Social platforms networks such Facebook continue encounter difficulties regarding Arabic content. Given importance developing reliable artificial intelligence that can reduce problems crimes associated with spread platforms, this study concerned evaluating performance tracking content Facebook. As an example, evaluates period October 2020 came known France’s cartoon controversy. Two corpora were designed. The first corpus comprised 347 posts deleted by Facebook, now Meta. second was composed 1,856 randomly selected using hashtag إلا رسول الله (except Prophet Allah). results indicate there considerable amount taken from or influenced Islamic religious discourse, but are unable address peculiar linguistic features also lack clarity defining constitutes “hate speech”. suggests networks, need adopt more consider properties Political thinkers scholars should involved