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Vito Latora

Publications and source records attributed to Vito Latora.

At least 127 records · Page 7Linked to original sources

The Ultimatum Game in Complex Networks

We address the problem of how cooperative (altruistic-like) behavior arises in natural and social systems by analyzing an ultimatum game in complex networks. Specifically, three types of players are considered: (a) empathetic, whose aspiration level and offer are equal, (b) pragmatic, who do not distinguish between the different roles and aim to obtain the same benefit, and (c) agents whose aspiration level and offer are independent. We analyze the asymptotic behavior of pure populations on different topologies using two kinds of strategic update rules. Natural selection, which relies on replicator dynamics, and Social Penalty, inspired in the Bak-Sneppen dynamics, in which players are subjected to a social selection rule penalizing not only the less fitted individuals, but also their first neighbors. We discuss the emergence of fairness in the different settings and network topologies.

physics.soc-ph↗

Traffic optimization in transport networks based on local routing

Congestion in transport networks is a topic of theoretical interest and practical importance. In this paper we study the flow of vehicles in urban street networks. In particular, we use a cellular automata model to simulate the motion of vehicles along streets, coupled with a congestion-aware routing at street crossings. Such routing makes use of the knowledge of agents about traffic in nearby roads and allows the vehicles to dynamically update the routes towards their destinations. By implementing the model in real urban street patterns of various cities, we show that it is possible to achieve a global traffic optimization based on local agent decisions.

physics.soc-ph↗

Enhancement of cooperation in highly clustered scale-free networks

We study the effect of clustering on the organization of cooperation, by analyzing the evolutionary dynamics of the Prisoner's Dilemma on scale-free networks with a tunable value of clustering. We find that a high value of the clustering coefficient produces an overall enhancement of cooperation in the network, even for a very high temptation to defect. On the other hand, high clustering homogeneizes the process of invasion of degree classes by defectors, decreasing the chances of survival of low densities of cooperator strategists in the network.

physics.soc-ph↗

Communities recognition in the Chesapeake Bay ecosystem by dynamical clustering algorithms based on different oscillators systems

We have recently introduced an efficient method for the detection and identification of modules in complex networks, based on the de-synchronization properties (dynamical clustering) of phase oscillators. In this paper we apply the dynamical clustering tecnique to the identification of communities of marine organisms living in the Chesapeake Bay food web. We show that our algorithm is able to perform a very reliable classification of the real communities existing in this ecosystem by using different kinds of dynamical oscillators. We compare also our results with those of other methods for the detection of community structures in complex networks.

q-bio.PE↗

Cluster structure of functional networks estimated from high-resolution EEG data

We study the topological properties of functional connectivity patterns among cortical areas in the frequency domain. The cortical networks were estimated from high-resolution EEG recordings in a group of spinal cord injured patients and in a group of healthy subjects, during the preparation of a limb movement. We first evaluate global and local efficiency, as indicators of the structural connectivity respectively at a global and local scale. Then, we use the Markov Clustering method to analyse the division of the network into community structures. The results indicate large differences between the injured patients and the healthy subjects. In particular, the networks of spinal cord injured patient exhibited a higher density of efficient clusters. In the Alpha (7-12 Hz) frequency band, the two observed largest communities were mainly composed by the cingulate motor areas with the supplementary motor areas, and by the pre-motor areas with the right primary motor area of the foot. This functional separation strengthens the hypothesis of a compensative mechanism due to the partial alteration in the primary motor areas because of the effects of the spinal cord injury.

q-bio.QM↗

Synchronization Properties of Network Motifs

We address the problem of understanding the variable abundance of 3-node and 4-node subgraphs (motifs) in complex networks from a dynamical point of view. As a criterion in the determination of the functional significance of a n-node subgraph, we propose an analytic method to measure the stability of the synchronous state (SSS) the subgraph displays. We show that, for undirected graphs, the SSS is correlated with the relative abundance, while in directed graphs the correlation exists only for some specific motifs.

physics.bio-ph↗

Entropy Rate of Diffusion Processes on Complex Networks

The concept of entropy rate for a dynamical process on a graph is introduced. We study diffusion processes where the node degrees are used as a local information by the random walkers. We describe analitically and numerically how the degree heterogeneity and correlations affect the diffusion entropy rate. In addition, the entropy rate is used to characterize complex networks from the real world. Our results point out how to design optimal diffusion processes that maximize the entropy for a given network structure, providing a new theoretical tool with applications to social, technological and communication networks.

cond-mat.stat-mech↗

Epcast: Controlled Dissemination in Human-based Wireless Networks by means of Epidemic Spreading Models

Epidemics-inspired techniques have received huge attention in recent years from the distributed systems and networking communities. These algorithms and protocols rely on probabilistic message replication and redundancy to ensure reliable communication. Moreover, they have been successfully exploited to support group communication in distributed systems, broadcasting, multicasting and information dissemination in fixed and mobile networks. However, in most of the existing work, the probability of infection is determined heuristically, without relying on any analytical model. This often leads to unnecessarily high transmission overheads. In this paper we show that models of epidemic spreading in complex networks can be applied to the problem of tuning and controlling the dissemination of information in wireless ad hoc networks composed of devices carried by individuals, i.e., human-based networks. The novelty of our idea resides in the evaluation and exploitation of the structure of the underlying human network for the automatic tuning of the dissemination process in order to improve the protocol performance. We evaluate the results using synthetic mobility models and real human contacts traces.

cs.NI↗

Disease spreading in populations of moving agents

We study the effect of motion on disease spreading in a system of random walkers which additionally perform long-distance jumps. A small percentage of jumps in the agent motion is sufficient to destroy the local correlations and to produce a large drop in the epidemic threshold, well explained in terms of a mean-field approximation. This effect is similar to the crossover found in static small-world networks, and can be furthermore linked to the structural properties of the dynamical network of agent interactions.

physics.soc-ph↗

Analysis of Self-Organized Criticality in the Olami-Feder-Christensen model and in real earthquakes

We perform a new analysis on the dissipative Olami-Feder-Christensen model on a small world topology considering avalanche size differences. We show that when criticality appears the Probability Density Functions (PDFs) for the avalanche size differences at different times have fat tails with a q-Gaussian shape. This behaviour does not depend on the time interval adopted and is found also when considering energy differences between real earthquakes. Such a result can be analytically understood if the sizes (released energies) of the avalanches (earthquakes) have no correlations. Our findings support the hypothesis that a self-organized criticality mechanism with long-range interactions is at the origin of seismic events and indicate that it is not possible to predict the magnitude of the next earthquake knowing those of the previous ones.

cond-mat.stat-mech↗

Street centrality vs. commerce and service locations in cities: a Kernel Density Correlation case study in Bologna, Italy

In previous research we defined a methodology for mapping centrality in urban networks. Such methodology, named Multiple Centrality Assessment (MCA), makes it possible to ascertain how each street is structurally central in a city according to several different notions of centrality, as well as different scales of "being central". In this study we investigate the case of Bologna, northern Italy, about how much higher street centrality statistically "determines" a higher presence of activities (shops and services). Our work develops a methodology, based on a kernel density evaluation, that enhances standard tools available in Geographic Information System (GIS) environment in order to support: 1) the study of how centrality and activities are distributed; 2) linear and non-linear statistical correlation analysis between centrality and activities, hereby named Kernel Density Correlation (KDC). Results offer evidence-based foundations that a strong correlation exists between centrality of streets, especially betweenness centrality, and the location of shops and services at the neighbourhood scale. This issue is at the heart of the current debate in urban planning and design towards the making of more sustainable urban communities for the future. Our results also support the "predictive" capability of the MCA model as a tool for sustainable urban design.

physics.soc-ph↗

Opinion formation models based on game theory

A way to simulate the basic interactions between two individuals with different opinions, in the context of strategic game theory, is proposed. Various games are considered, which produce different kinds of opinion formation dynamics. First, by assuming that all individuals (players) are equals, we obtain the bounded confidence model of continuous opinion dynamics proposed by Deffuant et al. In such a model a tolerance threshold is defined, such that individuals with difference in opinion larger than the threshold can not interact. Then, we consider that the individuals have different inclinations to change opinion and different abilities in convincing the others. In this way, we obtain the so-called ``Stubborn individuals and Orators'' (SO) model, a generalization of the Deffuant et al. model, in which the threshold tolerance is different for every couple of individuals. We explore, by numerical simulations, the dynamics of the SO model, and we propose further generalizations that can be implemented.

physics.soc-ph↗

Opinion dynamics and synchronization in a network of scientific collaborations

In this paper we discuss opinion dynamics in the Opinion Changing Rate (OCR) model, recently proposed (A.Pluchino, V.Latora and A.Rapisarda Int. J. Mod. Phys. C, 16, No.4, 515-531 (2005)). The OCR model allows to study whether and how a group of social agents, with a different intrinsic tendency rate to change opinion, finds agreement. In particular, we implement the OCR model on a small graph describing the topology of a real social system. The nodes of the graph are scientists partecipating to the Tepoztlan conference, celebrating Alberto Robledo's 60th birthday, and the links are based on coauthorship in scientific papers. We study how opinions evolve in time according to the frequency rates of the nodes, to the coupling term, and also to the presence of group structures.

physics.soc-ph↗

Multifractal analysis of Mt. St. Helens seismicity as a tool for identifying eruptive activity

We present a multifractal analysis of Mount St. Helens seismic activity during 1980-2002. The seismic time distribution is studied in relation to the eruptive activity, mainly marked by the 1980 major explosive eruptions and by the 1980-1986 dome building eruptions. The spectrum of the generalized fractal dimensions, i.e. Dq vs q, extracted from the data, allows us to identify two main earthquake time-distribution patterns. The first one exhibits a multifractal clustering correlated to the intense seismic swarms of the dome building activity. The second one is characterized by an almost constant value of Dq 1, as for a random uniform distribution. The time evolution of Dq (for q=0,2) calculated on a fixed number of events window and at different depths, shows that the brittle mechanical response of the shallow layers to rapid magma intrusions, during the eruptive periods, is revealed by sharp changes, acting at a short time scale (order of days), and by the lowest values of Dq (0.3). Conversely, for deeper earthquakes, characterized by intense seismic swarms, Dq do not show obvious changes during the whole analyzed period, suggesting that the earthquakes, related to the deep magma supply system, are characterized by a minor degree of clustering, which is independent of the eruptive activity.

physics.geo-ph↗

Compromise and Synchronization in Opinion Dynamics

We discuss two models of opinion dynamics. First wepresent a brief review of the Hegselmann and Krause (HK) compromise model in two dimensions, showing that it is possible to simulate the dynamics in the limit of an infinite number of agents by solving numerically a rate equation for a continuum distribution of opinions. Then, we discuss the Opinion Changing Rate (OCR) model, which allows to study under which conditions a group of agents with a different natural tendency (rate) to change opinion can find the agreement. In the context of the this model, consensus is viewed as a synchronization process.

physics.soc-ph↗

Effective spin-glass Hamiltonian for the anomalous dynamics of the HMF model

We discuss an effective spin-glass Hamiltonian which can be used to study the glassy-like dynamics observed in the metastable states of the Hamiltonian Mean Field (HMF) model. By means of the Replica formalism, we were able to find a self-consistent equation for the glassy order parameter which reproduces, in a restricted energy region below the phase transition, the microcanonical simulations for the polarization order parameter recently introducted in the HMF model.

cond-mat.stat-mech↗

Centrality Measures in Spatial Networks of Urban Streets

We study centrality in urban street patterns of different world cities represented as networks in geographical space. The results indicate that a spatial analysis based on a set of four centrality indices allows an extended visualization and characterization of the city structure. Planned and self-organized cities clearly belong to two different universality classes. In particular, self-organized cities exhibit scale-free properties similar to those found in the degree distributions of non-spatial networks.

physics.soc-ph↗

The Backbone of a City

Recent studies have revealed the importance of centrality measures to analyze various spatial factors affecting human life in cities. Here we show how it is possible to extract the backbone of a city by deriving spanning trees based on edge betweenness and edge information. By using as sample cases the cities of Bologna and San Francisco, we show how the obtained trees are radically different from those based on edge lengths, and allow an extended comprehension of the ``skeleton'' of most important routes that so much affects pedestrian/vehicular flows, retail commerce vitality, land-use separation, urban crime and collective dynamical behaviours.

physics.soc-ph↗