University of Cambridge > > Computer Laboratory Systems Research Group Seminar > Multi-relational Organization of Large-scale Social Networks in an Online World

Multi-relational Organization of Large-scale Social Networks in an Online World

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The capacity to collect fingerprints of individuals in online media has revolutionized the way researchers explore social systems. These systems can be seen as a non-linear superposition of a multitude of large, complex social networks, where nodes represent individuals and links capture all sorts of different social relations. Much emphasis has been put on the network topology of social interactions, however, the multi-dimensional nature of these interactions has largely been ignored in empirical studies, mostly because of lack of data. For the first time here we analyze a complete, multi-relational, large social network of a society consisting of the 300,000 odd players of a massive multiplayer online game. We extract networks of six different types of one-to-one interactions between the players. Three of them carry a positive connotation (friendship, communication, trade), three a negative (enmity, armed aggression, punishment). We first analyze these types of networks as separate entities and find that negative interactions differ from positive interactions by their lower reciprocity, weaker clustering and fatter-tail degree distribution. We then proceed to explore how the inter-dependence of different network types determines the organization of the social system. In particular we study correlations, overlap and causality between different types of links and demonstrate the tendency of individuals to play different roles in different networks. Finally we present empirical large-scale verification of the long-standing structural balance theory, by focussing on the specific multiplex network of friendship and enmity relations.

Bio: Renaud Lambiotte holds a PhD in physics from Université Libre de Bruxelles. He is currently research associate in the department of Mathematics at Imperial College London. His research field includes non-equilibrium statistical physics and complex networks, with applications in social systems and neuroscience. Previous works include the analysis of large-scale social networks (mobile phones and online games), the modeling of spatial diffusion of social agents, the detection of dense modules in large networks and their effect on information diffusion and knowledge creation.


This talk is part of the Computer Laboratory Systems Research Group Seminar series.

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