With the proliferation of terrorist/extremist websites on the World Wide Web, it has become progressively more crucial to detect and analyze the content on these websites. Accordingly, the volume of previous research focused on identifying the techniques and activities of terrorist/extremist groups, as revealed by their sites on the so-called dark web, has also grown.
This study presents a review of the techniques used to detect and process the content of terrorist/extremist sites on the dark web. Forty of the most relevant data sources were examined, and various techniques were identified among them.
Based on this review, it was found that methods of feature selection and feature extraction can be used as topic modeling with content analysis and text clustering.
At the end of the review, present the current state-of-the- art and certain open issues associated with Arabic dark Web content analysis.