Detection of the Elite Structure in a Virtual Multiplex Social System by Means of a Generalised K-Core

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 -core algorithm that allows to identify a social core that is composed of well-connected hubs together 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 -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 -core and the recently introduced -core, the elites of the different ’nations’ present in the game are perfectly identified as modules of the generalised -core. Interesting sudden shifts in the composition of the elite cores are observed at deep levels. We show that elite detection with the traditional -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.

The structure and dynamics of multilayer networks

“…Finally, Ref. [422] tackles the problem of detecting elite structures in the Pardus network, i.e. subgroups of individuals that have the ability of influencing the behavior of others.…”

The Multiplex Dependency Structure of Financial Markets

“…The importance of considering multiple types of human interactions has been more recently demonstrated in different social networks, from terrorist organizations [14] to online communities; in all these cases, multilayer analyses unveil a rich topological structure [17], outperforming single-layer analyses in terms of network modeling and prediction as well [18,19]. In particular, multilayer community detection in social networks has been shown to be more effective than single-layer approaches [20]; similar results have been reported for community detection on the World Wide Web [21,22] and citation networks [23].…”

Predicting the Currency Market in Online Gaming via Lexicon-Based Analysis on Its Online Forum

“…Various approaches to analyzing the structure and dynamic evolution of social networks in virtual worlds have been developed and have yielded significant findings [23,24]. Related studies based on these findings have been conducted from a variety of perspectives [25][26][27][28][29][30].…”