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arXiv2011

Evolutionary method for finding communities in bipartite networks

An important step in unveiling the relation between network structure and dynamics defined on networks is to detect communities, and numerous methods have been developed separately to identify community structure in different classes of networks, such as unipartite networks, bipartite networks, and directed networks. We show that both unipartite and directed networks can be represented as bipartite networks, and their modularity is completely consistent with that for bipartite networks, the detection of modular structure on which can be reformulated as modularity maximization. To optimize the bipartite modularity, we develop a modified adaptive genetic algorithm (MAGA), which is shown to be especially efficient for community structure detection. The high efficiency of the MAGA is based on the following three improvements we make. First, we introduce a different measure for the informativeness of a locus instead of the standard deviation, which can exactly determine which loci mutate. This measure is the bias between the distribution of a locus over the current population and the uniform distribution of the locus, i.e., the Kullback-Leibler divergence between them. Second, we develop a reassignment technique for differentiating the informative state a locus has attained from the random state in the initial phase. Third, we present a modified mutation rule which by incorporating related operation can guarantee the convergence of the MAGA to the global optimum and can speed up the convergence process. Experimental results show that the MAGA outperforms existing methods in terms of modularity for both bipartite and unipartite networks.

physics.data-an↗

arXiv2011

Analyzing the Facebook Friendship Graph

Online Social Networks (OSN) during last years acquired a huge and increasing popularity as one of the most important emerging Web phenomena, deeply modifying the behavior of users and contributing to build a solid substrate of connections and relationships among people using the Web. In this preliminary work paper, our purpose is to analyze Facebook, considering a significant sample of data reflecting relationships among subscribed users. Our goal is to extract, from this platform, relevant information about the distribution of these relations and exploit tools and algorithms provided by the Social Network Analysis (SNA) to discover and, possibly, understand underlying similarities between the developing of OSN and real-life social networks.

cs.SI↗

arXiv2011

Layered Label Propagation: A MultiResolution Coordinate-Free Ordering for Compressing Social Networks

We continue the line of research on graph compression started with WebGraph, but we move our focus to the compression of social networks in a proper sense (e.g., LiveJournal): the approaches that have been used for a long time to compress web graphs rely on a specific ordering of the nodes (lexicographical URL ordering) whose extension to general social networks is not trivial. In this paper, we propose a solution that mixes clusterings and orders, and devise a new algorithm, called Layered Label Propagation, that builds on previous work on scalable clustering and can be used to reorder very large graphs (billions of nodes). Our implementation uses overdecomposition to perform aggressively on multi-core architecture, making it possible to reorder graphs of more than 600 millions nodes in a few hours. Experiments performed on a wide array of web graphs and social networks show that combining the order produced by the proposed algorithm with the WebGraph compression framework provides a major increase in compression with respect to all currently known techniques, both on web graphs and on social networks. These improvements make it possible to analyse in main memory significantly larger graphs.

cs.DS↗

arXiv2010

Contributions of the United Nations Office for Outer Space Affairs to the International Space Weather Initiative (ISWI)

In 2010, the United Nations Committee on the Peaceful Uses of Outer Space began consideration of a new agenda item under a three-year work plan on the International Space Weather Initiative (ISWI). The main objectives of ISWI are to contribute to the development of the scientific insight necessary to improve understanding and forecasting capabilities of space weather as well as to education and public outreach. The United Nations Programme on Space Applications, implemented by the Office for Outer Space Affairs, is implementing ISWI in the framework of its United Nations Basic Space Science Initiative (UNBSSI), a long-term effort, launched in 1991, for the development of basic space science and for international and regional cooperation in this field on a worldwide basis, particularly in developing countries. UNBSSI encompassed a series of workshops, held from 1991 to 2004, which addressed the status of basic space science in Africa, Asia and the Pacific, Latin America and the Caribbean, and Western Asia. As a result several small astronomical research facilities have been inaugurated and education programmes at the university level were established. Between 2005 and 2009, the UNBSSI activities were dedicated to promoting activities related to the International Heliophysical Year 2007 (IHY), which contributed to the establishment of a series of worldwide ground-based instrument networks, a node of which is also operated by the Office for Outer Space Affairs. Building on these accomplishments, UNBSSI is now focussing on the ISWI.

astro-ph.IM↗

arXiv2010

Zipf's law and maximum sustainable growth

Zipf's law states that the number of firms with size greater than S is inversely proportional to S. Most explanations start with Gibrat's rule of proportional growth but require additional constraints. We show that Gibrat's rule, at all firm levels, yields Zipf's law under a balance condition between the effective growth rate of incumbent firms (which includes their possible demise) and the growth rate of investments in entrant firms. Remarkably, Zipf's law is the signature of the long-term optimal allocation of resources that ensures the maximum sustainable growth rate of an economy.

physics.soc-ph↗

arXiv2013

Generation of degree-correlated networks using copulas

Dynamical processes on complex networks such as information propagation, innovation diffusion, cascading failures or epidemic spreading are highly affected by their underlying topologies as characterized by, for instance, degree-degree correlations. Here, we introduce the concept of copulas in order to artificially generate random networks with an arbitrary degree distribution and a rich a priori degree-degree correlation (or `association') structure. The accuracy of the proposed formalism and corresponding algorithm is numerically confirmed. The derived network ensembles can be systematically deployed as proper null models, in order to unfold the complex interplay between the topology of real networks and the dynamics on top of them.

physics.data-an↗

arXiv2011

The Triple Helix, Quadruple Helix, . . ., and an N-tuple of Helices: Explanatory Models for Analyzing the Knowledge-based Economy?

Using the Triple Helix model of university-industry-government relations, one can measure the extent to which innovation has become systemic instead of assuming the existence of national (or regional) systems of innovations on a priori grounds. Systemness of innovation patterns, however, can be expected to remain in transition because of integrating and differentiating forces. Integration among the functions of wealth creation, knowledge production, and normative control takes place at the interfaces in organizations, while exchanges on the market, scholarly communication in knowledge production, and political discourse tend to differentiate globally. The neo-institutional and the neo-evolutionary versions of the Triple Helix model enable us to capture this tension reflexively. Empirical studies inform us whether more than three helices are needed for the explanation. The Triple Helix indicator can be extended algorithmically, for example, with local-global as a fourth dimension or, more generally, to an N-tuple of helices.

nlin.AO↗

arXiv2011

Diffusion and Cascading Behavior in Random Networks

The spread of new ideas, behaviors or technologies has been extensively studied using epidemic models. Here we consider a model of diffusion where the individuals' behavior is the result of a strategic choice. We study a simple coordination game with binary choice and give a condition for a new action to become widespread in a random network. We also analyze the possible equilibria of this game and identify conditions for the coexistence of both strategies in large connected sets. Finally we look at how can firms use social networks to promote their goals with limited information. Our results differ strongly from the one derived with epidemic models and show that connectivity plays an ambiguous role: while it allows the diffusion to spread, when the network is highly connected, the diffusion is also limited by high-degree nodes which are very stable.

math.PR↗

arXiv2012

Modeling urban housing market dynamics: can the socio-spatial segregation preserve some social diversity?

Addressing issues of social diversity, we introduce a model of housing transactions between agents who are heterogeneous in their willingness to pay. A key assumption is that agents' preferences for a location depend on both an intrinsic attractiveness and on the social characteristics of the neighborhood. The stationary space distribution of income is analytically and numerically characterized. The main results are that socio-spatial segregation occurs if -- and only if -- the social influence is strong enough, but even so, some social diversity is preserved at most locations. Comparison with data on the Paris housing market shows that the results reproduce general trends of price distribution and spatial income segregation.

physics.soc-ph↗

arXiv2012

Generating constrained random graphs using multiple edge switches

The generation of random graphs using edge swaps provides a reliable method to draw uniformly random samples of sets of graphs respecting some simple constraints, e.g. degree distributions. However, in general, it is not necessarily possible to access all graphs obeying some given con- straints through a classical switching procedure calling on pairs of edges. We therefore propose to get round this issue by generalizing this classical approach through the use of higher-order edge switches. This method, which we denote by "k-edge switching", makes it possible to progres- sively improve the covered portion of a set of constrained graphs, thereby providing an increasing, asymptotically certain confidence on the statistical representativeness of the obtained sample.

cs.SI↗

arXiv2011

London house prices are power-law distributed

We explore the house price distributions for the English cities of London, Manchester, Bristol, Newcastle, Birmingham and Leeds. We find Pareto (power law) behaviour in their upper tails, which is clearly distinct from lognormal and gamma distributions in the cases of London, Manchester and Newcastle. For London, the city with the lowest power, this is a striking match with that found in the wealth distribution of the super-rich. We propose an index of Housing Wealth Inequality based on the Pareto exponent and analogous to the Gini coefficient, and comment on its possible uses.

physics.soc-ph↗

arXiv2010

Effect of Driver Behavior on Spatiotemporal Congested Traffic Patterns at Highway Bottlenecks in the Framework of Three-Phase Traffic Theory

We present results of numerical simulations of the effect of driver behavior on spatiotemporal congested traffic patterns that result from traffic breakdown at an on-ramp bottleneck. The simulations are made with the Kerner-Klenov stochastic traffic flow model in the framework of three-phase traffic theory. Different diagrams of congested patterns at the bottleneck associated with different driver behavioral characteristics are found and compared each other. An adaptive cruise control (ACC) in the framework of three-phase traffic theory introduced by the author (called a "driver alike ACC" (DA-ACC)) is discussed. The effect of DA-ACC-vehicles on traffic flow, in which without the DA-ACC-vehicles traffic congestion occurs at the bottleneck, is numerically studied. We show that DA-ACC-vehicles improve traffic flow considerably without any reduction in driving comfort. It is found that there is a critical percentage of DA-ACC-vehicles in traffic flow: If the percentage of the DA-ACC-vehicle exceeds the critical one no traffic breakdown occurs at the bottleneck. A criticism of a recent "criticism of three-phase traffic theory" is presented

physics.soc-ph↗

arXiv2011

"Structuration" by Intellectual Organization: The Configuration of Knowledge in Relations among Structural Components in Networks of Science

Using aggregated journal-journal citation networks, the measurement of the knowledge base in empirical systems is factor-analyzed in two cases of interdisciplinary developments during the period 1995-2005: (i) the development of nanotechnology in the natural sciences and (ii) the development of communication studies as an interdiscipline between social psychology and political science. The results are compared with a case of stable development: the citation networks of core journals in chemistry. These citation networks are intellectually organized by networks of expectations in the knowledge base at the specialty (that is, above-journal) level. This "structuration" of structural components (over time) can be measured as configurational information. The latter is compared with the Shannon-type information generated in the interactions among structural components: the difference between these two measures provides us with a measure for the redundancy generated by the specification of a model in the knowledge base of the system. This knowledge base incurs (against the entropy law) to variable extents on the knowledge infrastructures provided by the observable networks of relations.

cs.DL↗

arXiv2011

Recorded punishment promotes cooperation in spatial prisoner's dilemma game

Previous studies suggest that punishment is a useful way to promote cooperation in the well-mixed public goods game, whereas it still lacks specific evidence that punishment maintains cooperation in spatial prisoner's dilemma game as well. To address this issue, we introduce a mechanism of recorded punishment, involved with memory and punishment, into spatial prisoner's dilemma game. We find that increasing punishment rate or memory length promotes the evolution of cooperation monotonously. Interestingly, compared with traditional version, recorded punishment will facilitate cooperation better through a recovery effect. Moreover, through examining the process of evolution, we provide an interpretation to this promotion phenomenon, namely, the recovery effect can be warranted by an evolution resonance of standard deviation of fitness coefficient. Finally, we confirm our results by studying the impact of uncertainty within strategy adoptions. We hope that our work may sharpen the understanding of the cooperative behavior in the society.

physics.soc-ph↗

arXiv2011

Social Norms for Online Communities

Sustaining cooperation among self-interested agents is critical for the proliferation of emerging online social communities, such as online communities formed through social networking services. Providing incentives for cooperation in social communities is particularly challenging because of their unique features: a large population of anonymous agents interacting infrequently, having asymmetric interests, and dynamically joining and leaving the community; operation errors; and low-cost reputation whitewashing. In this paper, taking these features into consideration, we propose a framework for the design and analysis of a class of incentive schemes based on a social norm, which consists of a reputation scheme and a social strategy. We first define the concept of a sustainable social norm under which every agent has an incentive to follow the social strategy given the reputation scheme. We then formulate the problem of designing an optimal social norm, which selects a social norm that maximizes overall social welfare among all sustainable social norms. Using the proposed framework, we study the structure of optimal social norms and the impacts of punishment lengths and whitewashing on optimal social norms. Our results show that optimal social norms are capable of sustaining cooperation, with the amount of cooperation varying depending on the community characteristics.

cs.SI↗

arXiv2011

A Round-Robin Tournament of the Iterated Prisoner's Dilemma with Complete Memory-Size-Three Strategies

In this paper the results of a simulation of a prisoner's dilemma robin-round tournament are presented. In the tournament each participating strategy plays an iterated prisoner's dilemma against each other strategy (round-robin) and as a variant also against itself. The participants of a tournament are all strategies that are deterministic and have the same size of memory with regard to their own and their opponent's past actions: up to three most recent actions of their opponent and up to two most recent actions of their own. A focus is set on the investigation of the influence of the number of iterations, details of the payoff matrix, and the influence of memory size. The main result is that for the tournament as carried out here, different strategies emerge as winners for different payoff matrices, even for different payoff matrices being similar judged on if they fulfill relations T + S = P + R or 2R > T + S. As a consequence of this result it is suggested that whenever the iterated prisoner's dilemma is used to model a real system that does not explicitly fix the payoff matrix, one should check if conclusions remain valid, when a different payoff matrix is used.

cs.GT↗

arXiv2011

Diffusion of Confidential Information on Networks

This is a natural generalization of the previous work by Dan, "Modeling and Simulation of Diffusion Phenomena on Social Networks," to appear in The proceedings of 2011 Third International Conference on Computer Modeling and Simulation. In this paper, we consider the diffusion phenomena of personal or secret information on the variety of networks, such as complete, random, stochastic and scale-free networks.

cs.SI↗

arXiv2013

Universality of competitive networks for weighted networks

In this paper, we propose a new model that allows us to investigate this competitive aspect of real networks in quantitative terms. Through theoretical analysis and numerical simulations, we find that the competitive network have the universality for a weighted network. The relation between parameters in the weighted network and the competitiveness in the competitive network is obtained. So we can use the expression of the degree distribution of the competitive model to calculate that and the strength of the weighted network directly. The analytical solution reveals that the degree distribution of the weighted network is correlated with the increment and initial value of edge weights, which is verified by numerical simulations. Moreover, the evolving pattern of a clustering coefficient along with network parameters such as the size of a network, an updating coefficient, an initial weight and the competitiveness are obtained by further simulations. Specially, it is necessary to point out that the initial weight plays equally significant role as updating coefficient in influencing the topological characteristics of the network.

physics.soc-ph↗