Abstract: In the past few years and as a result of the enormous spreading of social media platforms worldwide, many radical groups tried to invade social media cyber space in order to disseminate their ideologies and destructive plans. This brutal invasion to society daily life style must be resisted as social media networks are interacted with on daily basis. As some violent radical groups such as ISIS has developed well designed propaganda strategies that enables them to recruit more members and supporters all over the world using social media facilities. So it is crucial to find an efficient way to detect the violent-radical accounts in social media networks. In this paper, an intelligent system that autonomously detects ISIS online community in Twitter social media platform is proposed. The proposed system analyzes both linguistic features and behavioral features such as hashtags, mentions and who they follow. The system consists of two main sub-systems, namely the crawling and the inquiring subsystems. The crawling subsystem uses the initially known ISIS-related accounts to establish an ISIS-account detector. The inquiring subsystem aims to detect Pro ISIS-accounts.

Ahmed I. A. Abd-Elaal, Ahmed Z. Badr and Hani M. K. Mahdi, “Detecting Violent Radical Accounts on Twitter” International Journal of Advanced Computer Science and Applications(IJACSA), 11(8), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110865

@article{Abd-Elaal2020,
title = {Detecting Violent Radical Accounts on Twitter},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110865},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110865},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {8},
author = {Ahmed I. A. Abd-Elaal and Ahmed Z. Badr and Hani M. K. Mahdi}
}