TOWARD A COMPREHENSIVE TERRORIST PREDICITION IN SOCIAL NETWORK

Social network analysis can play significant role in detecting human personality. Consequently, special personality characteristics can be analyzed to predict potential terrorism actions. These features could be conducted by using different social representations such as athletics, social and regional characteristics and so on . Data can be mined to result set of people with common features and categories. Based on that , people can be clustered according to their affiliation clustering on scale of dangerous and peaceful ones. Herein, a social network partitioning and clustering model is implemented to detect how close is a citizen to terrorism or a terrorist