Detection of the elite structure in a virtual multiplex social system by means of a generalized K-core

Corominas-Murtra, B., Fuchs, B., & Thurner, S. (2014). Detection of the elite structure in a virtual multiplex social system by means of a generalized K-core. PLoS ONE 9 (12) e112606. 10.1371/journal.pone.0112606.

Preview

Text Detection of the Elite Structure in a Virtual Multiplex Social System by Means of a Generalised K-Core.PDF - Published Version Available under License Creative Commons Attribution. Download (954kB) | Preview

Abstract

Elites are subgroups of individuals within a society that have the ability and means to influence, lead, govern, and shape societies. Members of elites are often well connected individuals, which enables them to impose their influence to many and to quickly gather, process, and spread information. Here we argue that elites are not only composed of highly connected individuals, but also of intermediaries connecting hubs to form a cohesive and structured elite-subgroup at the core of a social network. For this purpose we present a generalization of the K-core algorithm that allows to identify a social core that is composed of well-connected hubs togethe with their 'connectors'. We show the validity of the idea in the framework of a virtual world defined by a massive multiplayer online game, on which we have complete information of various social networks. Exploiting this multiplex structure we find that the hubs of the generalised K-core identify those individuals that are high social performers in terms of a series of indicators that are available in the game. In addition, using a combined strategy which involves the generalised K-core and the recently introduced M-core, the elites of the different 'nations' present in the game are perfectly identified as modules of the generalised K-core. Interesting sudden shifts in the composition of the elite cores are observed at deep levels. We show that elite detection with the traditional K-core is not possible in a reliable way. The proposed method might be useful in a series of more general applications, such as community detection.

Actions (login required)

View Item