Analyzing covert social network foundation behind terrorism disaster

This paper addresses a method to analyze the covert social network foundation hidden behind the terrorism disaster. It is to solve a node discovery problem, which means to discover a node, which functions relevantly in a social network, but escaped from monitoring on the presence and mutual relationship of nodes. The method aims at integrating the expert investigator's prior understanding, insight on the terrorists' social network nature derived from the complex graph theory, and computational data processing. The social network responsible for the 9/11 attack in 2001 is used to execute simulation experiment to evaluate the performance of the method.Comment: 17pages, 10 figures, submitted to Int. J. Services Science

SOCIAL NETWORKS OF THE ITALIAN MAFIA; THE STRONG AND WEAK PARTS

In this paper, it is argued that well-built, social network system has enabled the Mafia to\ud reach a certain level of success through three main networks: members, local people, and\ud politicians. I assert that the role of the executive power of the state has been partially\ud supportive in this success. Moreover, this paper also concludes that to combat different\ud Mafia groups, it is essential to know their strong and weak parts. Consequently, it is found\ud that their well-built network system does not solely comprise of strong parts but that the\ud weak parts also exist, albeit, that they have not yet played a defective role in the resolution of\ud the Mafia. Therefore, this paper suggests that the illustration of both the strong and weak\ud parts of these networks can have prominent and assisting role in the combat against the\ud Mafia phenomenon in the future, either by strengthening the weak parts or by weakening the\ud strong parts of its networks

Social Network Intelligence Analysis to Combat Street Gang Violence

In this paper we introduce the Organization, Relationship, and Contact Analyzer (ORCA) that is designed to aide intelligence analysis for law enforcement operations against violent street gangs. ORCA is designed to address several police analytical needs concerning street gangs using new techniques in social network analysis. Specifically, it can determine "degree of membership" for individuals who do not admit to membership in a street gang, quickly identify sets of influential individuals (under the tipping model), and identify criminal ecosystems by decomposing gangs into sub-groups. We describe this software and the design decisions considered in building an intelligence analysis tool created specifically for countering violent street gangs as well as provide results based on conducting analysis on real-world police data provided by a major American metropolitan police department who is partnering with us and currently deploying this system for real-world use