[Colloq] Colloquium on Wed, Oct 30: An Axiomatic Approach to Elites of Social Networks

[Francoise Niang]

Title: From Caesar to Twitter - An Axiomatic Approach to Elites of
       Social Networks

Speaker: Chen Avin
         Ben Gurion University, Israel
         (currently on sabbatical at Brown University)               

Abstract:

In many societies there is an elite, a relatively small group of powerful individuals that is well connected and highly influential. Since the ancient days of Julius Caesar’s senate to the recent days of celebrities on Twitter, the size of the elite is a result of conflicting social forces competing to increase or decrease it.

The main contribution of this paper is the answer to the novel question about the size of the elite in equilibrium. We take an axiomatic approach to solve this: assuming that elite exists and it is influential, stable and either of minimal or dense we prove that its size must be of size Θ(√m) (where m is the number of edges in the network).

As an approximation for the elite we then present an empirical study of the sub-graph formed by the highest degree nodes, also known as the rich-club. Our empirical findings indicate that elite properties such as a size of Θ(√m), disproportionate influence, stability and density are universal properties and should join an increasing list of common phenomenon that complex systems share such as “small world”, power law degree distributions, high clustering, etc.

Joint work with Zvi Lotker, Yvonne-Anne Pignolet and Itzik Turkel

http://arxiv.org/abs/1111.3374

Host: Rajmohan Rajaraman

Bio:

Dr. Chen Avin received the B.Sc. degree in Communication Systems Engineering from Ben Gurion University, Israel, in 2000. He received the M.S. and Ph.D. degrees in computer science from the University of California, Los Angeles (UCLA) in 2003 and 2006 respectively. He is an associate professor in the Department of Communication Systems Engineering at the Ben Gurion University for which he joined on October 2006. His current research interests are: graphs and networks algorithms, modeling and analysis with emphasis on complex systems and randomize algorithms.