Task Description

The Author Profiling and Deception Detection in Arabic consists of two tasks

Task 1. Author Profiling in Arabic Tweets

Author profiling distinguishes between classes of authors studying how language is shared by people. This helps in identifying profiling aspects such as age, gender, and language variety, among others. The focus of this task is to identify the age, gender, and language variety of Arabic Twitter users.

NOTE: Although we suggest to participate in all the subtasks, it is possible participating only in some of them.

Task 2. Deception Detection in Arabic Texts

We can consider that a message is deceptive when it is intentionally written trying to sound authentic. The focus of the task is on deception detection in Arabic on two different genres: Twitter and news headlines..

Tasks coordinators

Author Profiling for Cyber-Security (ARAP)


In the framework of the project Arabic Author Profiling for Cyber-Security (ARAP), we aim at preventing cyber-threats using machine learning (see next figure). To this end, we monitor social media to early detect threatening messages and, in such a case, to profile the authors behind. Profiling potential terrorists from messages shared in social media may allow detecting communities whose aim is to undermine the security of others. Nonetheless, we must be aware of false positives, i.e., potential threatening messages that are actually deceptive, ironic or humorous.

The research project has been funded under grant NPRP 9-175-1-033 from the Qatar National Research Fund (a member ofQatar Foundation).


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