Node discovery problem for a social network

This paper presents a practical heuristic algorithm to address a node discovery problem. The node discovery problem is to discover a clue on the person, who does not appear in the observed records, but is relevant functionally in affecting decision-making and behavior of an organization. We define two topological relevance of a node in a social network (global and local relevance). Association between the topological relevance and the functional relevance is studied with a few example networks in criminal organizations. We propose a heuristic algorithm to infer an invisible, functionally relevant person. Its performance (precision, recall, and F value) is demonstrated with a simulation experiment using a network derived from the Watts-Strogatz (WS) model. 1 Node discovery problem The activity of an organization is often under influence from an invisible relevant person. The term, invisible, means that the influence is not seen directly by the method applied in the observation procedure. This phenomenon arises intentionally or unintentionally. Let us show 2 examples. 1. Criminal organization: A commander tries to conceal himself from leaving any traces in communication and meeting logs, which are the basic intelligence to the police. Otherwise, exposure and arrest of a relevant pilot would have been a fatal damage to the terrorist organization in the 9/11 attack. 2. Manufacturing company: A sales person happens to be a close friend of an expertise factory engineer through a common friend: a product designer. ∗Corresponding author: Yoshiharu Maeno, Graduate School of Systems Management, Tsukuba University, address: Otsuka 3-29-1, Bunkyo-ku, Tokyo 112-0012 Japan, telephone: +81-3-3942-6918, email: [email protected]