Co-occurrence networks in social and economic systems

Heterogeneity is a ubiquitous aspect of many social and economic complex systems. The analysis and modeling of heterogeneous systems is quite difficult because each economic and social actor is characterized by different attributes and it is usually acting on a multiplicity of time scales. We use statistically validated networks [1], a recently introduced method to validate links in a bipartite system, to investigate heterogeneous social and economic systems. Specifically, we investigate the classic movie-actor system [1] and the trading activity of individual investors of Nokia stock [2]. The method is unsupervised and allows constructing networks of social actors where the links indicate co-occurrence of events or decisions. Each link is statistically validated against a null hypothesis taking into account system heterogeneity. Community detection is performed on the statistically validated networks and the communities (partitions) obtained are investigated with respect to the over-expression or under-expression of the attributes characterizing the social actors and/or their activities [3].

 [1] Michele Tumminello, Salvatore Miccichè, Fabrizio Lillo, Jyrki Piilo, Rosario N Mantegna (2011) Statistically Validated Networks in Bipartite Complex Systems. PLoS ONE 6(3): e17994.

[2] Michele Tumminello, Fabrizio Lillo, Jyrki Piilo, and Rosario N. Mantegna, Identification of clusters of investors from their real trading activity in a financial market (2012) New J. Phys. 14 013041

[3] Michele Tumminello , Salvatore Miccichè , Fabrizio Lillo , Jan Varho , Jyrki Piilo and  Rosario N Mantegna, Community characterization of heterogeneous complex systems (2011) J. Stat. Mech. P01019