Copyright (c) 2010 All rights reserved. http://works.bepress.com/lambiotte Recent documents in Renaud Lambiotte en-us Tue, 14 Dec 2010 01:31:08 PST 3600 http://works.bepress.com/lambiotte/5 http://works.bepress.com/lambiotte/5 Sun, 12 Dec 2010 08:37:11 PST The capacity to collect fingerprints of individuals in online media has revolutionized the way researchers explore human society. Social systems can be seen as a nonlinear superposition of a multitude of complex social networks, where nodes represent individuals and links capture a variety of different social relations. Much emphasis has been put on the network topology of social interactions, however, the multidimensional nature of these interactions has largely been ignored, mostly because of lack of data. Here, for the first time, we analyze a complete, multirelational, 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 explore how the interdependence of different network types determines the organization of the social system. In particular, we study correlations and overlap between different types of links and demonstrate the tendency of individuals to play different roles in different networks. As a demonstration of the power of the approach, we present the first empirical large-scale verification of the long-standing structural balance theory, by focusing on the specific multiplex network of friendship and enmity relations. Renaud Lambiotte complex networks http://works.bepress.com/lambiotte/4 http://works.bepress.com/lambiotte/4 Thu, 06 Mar 2008 06:33:21 PST Social, technological and information systems can often be described in terms of complex networks that have a topology of interconnected nodes that combines organization and randomness. The typical size of large networks such as social network services, mobile phone networks or the web now counts in millions when not billions of nodes and these scales demand new methods to retrieve comprehensive information from their structure. A promising approach consists in decomposing the networks into sub-units or communities, which are sets of highly connected nodes. The identification of these communities is of crucial importance as they may help to uncover a-priori unknown functional modules such as topics in information networks or cyber-communities in social networks. Moreover, the resulting meta-network, whose nodes are the communities, may then be used to visualize the original network structure. Here we propose a simple community detection method that reveals the hierarchical community structure of networks and that outperforms all other known community detection methods. We use our method to identify language communities and analyze community interactions in a Belgian mobile phone network of 2.6 million customers and we apply it to a web network of 118 million nodes and more than one billion links. Vincent D. Blondel complex networks http://works.bepress.com/lambiotte/3 http://works.bepress.com/lambiotte/3 Mon, 15 Oct 2007 01:43:24 PDT We focus on the dynamics of a Brownian particle whose mass fluctuates. First we show that the behaviour is similar to that of a Brownian particle moving in a fluctuating medium, as studied by Beck. By performing numerical simulations of the Langevin equation, we check the theoretical predictions derived in the adiabatic limit, and study deviations outside this limit. We compare the mass velocity distribution with truncated Tsallis distributions and find excellent agreement if the masses are chi-squared distributed. We also consider the diffusion of the Brownian particle by studying a Bernoulli random walk with fluctuating walk length in one dimension. We observe the time dependence of the position distribution kurtosis and find interesting behaviours. We point out a few physical cases where the mass fluctuation problem could be encountered as a first approximation for agglomeration-fracture non equilibrium processes. Marcel Ausloos Kinetic theory http://works.bepress.com/lambiotte/1 http://works.bepress.com/lambiotte/1 Mon, 15 Oct 2007 01:34:21 PDT We introduce the vacillating voter model in which each voter consults two neighbors to decide its state, and changes opinion if it disagrees with either neighbor. This irresolution leads to a global bias toward zero magnetization. In spatial dimension $d>1$, anti-coarsening arises in which the linear dimension $L$ of minority domains grows as $t^{1/(d+1)}$. One consequence is that the time to reach consensus scales exponentially with the number of voters. Renaud Lambiotte Opinion formation