Building an Arabic Social Corpus for Dangerous Profile Extraction on Social Networks

Amal Rekik, Hanen Ameur, Amal Abid, Atika Mbarek, Wafa Kardamine, Salma Jamoussi, Abdelmajid Ben Hamadou


Social networks are considered today as revolutionary tools of communication that have a tremendous impact on our lives. However, these tools can be manipulated by vicious users namely terrorists. The process of collecting and analyzing such profiles is a considerably challenging task which has not yet been well established. For this purpose, we propose, in this paper, a new method for data extraction and annotation of suspicious users from social networks threatening the national security. Our method allows constructing a rich Arabic corpus designed for detecting terrorist users spreading on social networks. The amendment of our corpora is ensured following a set of rules defined by a domain expert. All these steps are described in details, and some typical examples are given. Also, some statistics are reported from the data collection and annotation stages as well as the evaluation of the annotated features based on the intra-agreement measurement between different experts.


Data collection, annotation guidelines, social networks, suspicious content, terrorist users, arabic social corpus

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