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Zhao K.,Northeastern University | Stehle J.,French National Center for Scientific Research | Bianconi G.,Northeastern University | Barrat A.,French National Center for Scientific Research | Barrat A.,Turin Networks
Physical Review E - Statistical, Nonlinear, and Soft Matter Physics | Year: 2011

The recent availability of data describing social networks is changing our understanding of the "microscopic structure" of a social tie. A social tie indeed is an aggregated outcome of many social interactions such as face-to-face conversations or phone calls. Analysis of data on face-to-face interactions shows that such events, as many other human activities, are bursty, with very heterogeneous durations. In this paper we present a model for social interactions at short time scales, aimed at describing contexts such as conference venues in which individuals interact in small groups. We present a detailed analytical and numerical study of the model's dynamical properties, and show that it reproduces important features of empirical data. The model allows for many generalizations toward an increasingly realistic description of social interactions. In particular, in this paper we investigate the case where the agents have intrinsic heterogeneities in their social behavior, or where dynamic variations of the local number of individuals are included. Finally we propose this model as a very flexible framework to investigate how dynamical processes unfold in social networks. © 2011 American Physical Society. Source

Lancichinetti A.,Turin Networks | Radicchi F.,Polytechnic University of Turin | Ramasco J.J.,Polytechnic University of Turin
Physical Review E - Statistical, Nonlinear, and Soft Matter Physics | Year: 2010

Nodes in real-world networks are usually organized in local modules. These groups, called communities, are intuitively defined as subgraphs with a larger density of internal connections than of external links. In this work, we define a measure aimed at quantifying the statistical significance of single communities. Extreme and order statistics are used to predict the statistics associated with individual clusters in random graphs. These distributions allows us to define one community significance as the probability that a generic clustering algorithm finds such a group in a random graph. The method is successfully applied in the case of real-world networks for the evaluation of the significance of their communities. © 2010 The American Physical Society. Source

Remlein P.,Poznan University of Technology | Jasinski M.,Poznan University of Technology | Perotti A.,Turin Networks
Electronics Letters | Year: 2012

The performance of multiuser systems employing coded continuous- phase modulation (CPM) in frequency-division multiplexed (FDM) uplink satellite communications is investigated. The spectral efficiency is improved reducing the inter-carrier frequency spacing. Since severe inter-channel interference (ICI) occurs in such cases, a simple iterative ICI cancellation algorithm is applied in conjunction with a bank of single-user (SU) receivers to perform demodulation and decoding. When modulation and coding parameters are suitably chosen, such a receiver achieves a performance close to the non-interfering multiuser case. ICI causes further degradation since the SU receivers are not perfectly matched to the received signal model. Moreover, the SU receivers require a perfect knowledge of the channel state information (CSI) in order to perform optimal demodulation in additive white Gaussian noise. To reduce the degradation caused by ICI, a new heuristic method for estimating the optimal CSI values to provide to the SU receiver is proposed. The proposed method is based on an approximation of the CSI vector provided to each SU receiver. Such a method proves useful since it leads to significant performance improvements of the considered schemes and exhibits a negligible complexity. © 2012 The Institution of Engineering and Technology. Source

Baronchelli A.,Polytechnic University of Catalonia | Gong T.,Max Planck Institute for Evolutionary Anthropology | Puglisi A.,National Research Council Italy | Puglisi A.,University of Rome La Sapienza | And 2 more authors.
Proceedings of the National Academy of Sciences of the United States of America | Year: 2010

The empirical evidence that human color categorization exhibits some universal patterns beyond superficial discrepancies across different cultures is a major breakthrough in cognitive science. As observed in the World Color Survey (WCS), indeed, any two groups of individuals develop quite different categorization patterns, but some universal properties can be identified by a statistical analysis over a large number of populations. Here, we reproduce the WCS in a numerical model in which different populations develop independently their own categorization systems by playing elementary language games.We find that a simple perceptual constraint shared by all humans, namely the human Just Noticeable Difference (JND), is sufficient to trigger the emergence of universal patterns that unconstrained cultural interaction fails to produce. We test the results of our experiment against real data by performing the same statistical analysis proposed to quantify the universal tendencies shown in the WCS [Kay P & Regier T. (2003) Proc. Natl. Acad. Sci. USA 100: 9085-9089], and obtain an excellent quantitative agreement. This work confirms that synthetic modeling has nowadays reached the maturity to contribute significantly to the ongoing debate in cognitive science. Source

Stehle J.,French National Center for Scientific Research | Barrat A.,French National Center for Scientific Research | Barrat A.,Turin Networks | Bianconi G.,Northeastern University
Physical Review E - Statistical, Nonlinear, and Soft Matter Physics | Year: 2010

We present a modeling framework for dynamical and bursty contact networks made of agents in social interaction. We consider agents' behavior at short time scales in which the contact network is formed by disconnected cliques of different sizes. At each time a random agent can make a transition from being isolated to being part of a group or vice versa. Different distributions of contact times and intercontact times between individuals are obtained by considering transition probabilities with memory effects, i.e., the transition probabilities for each agent depend both on its state (isolated or interacting) and on the time elapsed since the last change in state. The model lends itself to analytical and numerical investigations. The modeling framework can be easily extended and paves the way for systematic investigations of dynamical processes occurring on rapidly evolving dynamical networks, such as the propagation of an information or spreading of diseases. © 2010 The American Physical Society. Source

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