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At least 307 records · Page 17Linked to original sources

arXiv2012

On amending the Maskin's sufficiency theorem by using complex numbers

The Maskin's theorem is a fundamental work in the theory of mechanism design. In this paper, we will propose a self-enforcing agreement by which agents can fight a bad social choice rule which satisfies monotonicity and no-veto if an additional condition is satisfied. The agreement is based on complex numbers and is justified if the designer receives messages from the agents through some communication channels (e.g., Internet). Under the assumption of complete information among agents, the designer cannot prevent the agents from signing such agreement. Thereby, the Maskin's sufficiency theorem is amended.

physics.soc-ph↗

arXiv2010

Active Learning for Hidden Attributes in Networks

In many networks, vertices have hidden attributes, or types, that are correlated with the networks topology. If the topology is known but these attributes are not, and if learning the attributes is costly, we need a method for choosing which vertex to query in order to learn as much as possible about the attributes of the other vertices. We assume the network is generated by a stochastic block model, but we make no assumptions about its assortativity or disassortativity. We choose which vertex to query using two methods: 1) maximizing the mutual information between its attributes and those of the others (a well-known approach in active learning) and 2) maximizing the average agreement between two independent samples of the conditional Gibbs distribution. Experimental results show that both these methods do much better than simple heuristics. They also consistently identify certain vertices as important by querying them early on.

stat.ML↗

arXiv2010

Reducing the Leak Rate from a Damaged Oil Well by Filling It with Dense Streamlined Objects

The enormous pressure lifting the column of oil in a leaking oil well can thwart efforts to seal the top of the well and prevent oil from rising. When the oil cannot be stopped completely, we propose to slow its flow by filling the well with a porous medium. That medium consists of countless small, dense, streamlined objects that are dropped into the well and descend through the rising oil at terminal velocity. The resulting heap of objects couples to the oil via viscous and drag forces, dissipating the oil's energy and upward momentum and significantly reducing its rate of flow.

physics.flu-dyn↗

arXiv2010

Predicting Failures in Power Grids: The Case of Static Overloads

Here we develop an approach to predict power grid weak points, and specifically to efficiently identify the most probable failure modes in static load distribution for a given power network. This approach is applied to two examples: Guam's power system and also the IEEE RTS-96 system, both modeled within the static Direct Current power flow model. Our algorithm is a power network adaption of the worst configuration heuristics, originally developed to study low probability events in physics and failures in error-correction. One finding is that, if the normal operational mode of the grid is sufficiently healthy, the failure modes, also called instantons, are sufficiently sparse, i.e. the failures are caused by load fluctuations at only a few buses. The technique is useful for discovering weak links which are saturated at the instantons. It can also identify generators working at the capacity and generators under capacity, thus providing predictive capability for improving the reliability of any power network.

math.OC↗

arXiv2011

Triadic closure in two-mode networks: Redefining the global and local clustering coefficients

As the vast majority of network measures are defined for one-mode networks, two-mode networks often have to be projected onto one-mode networks to be analyzed. A number of issues arise in this transformation process, especially when analyzing ties among nodes' contacts. For example, the values attained by the global and local clustering coefficients on projected random two-mode networks deviate from the expected values in corresponding classical one-mode networks. Moreover, both the local clustering coefficient and constraint (structural holes) are inversely associated to nodes' two-mode degree. To overcome these issues, this paper proposes redefinitions of the clustering coefficients for two-mode networks.

physics.soc-ph↗

arXiv2010

A unified approach to mapping and clustering of bibliometric networks

In the analysis of bibliometric networks, researchers often use mapping and clustering techniques in a combined fashion. Typically, however, mapping and clustering techniques that are used together rely on very different ideas and assumptions. We propose a unified approach to mapping and clustering of bibliometric networks. We show that the VOS mapping technique and a weighted and parameterized variant of modularity-based clustering can both be derived from the same underlying principle. We illustrate our proposed approach by producing a combined mapping and clustering of the most frequently cited publications that appeared in the field of information science in the period 1999-2008.

cs.DL↗

arXiv2014

A model of human population motion

We introduce a basic model for human mobility that accounts for the different dynamics arising from individuals embarking on short trips (and returning to their home locations) and individuals relocating to a new home. The differences between the two modes of motion comes to light on contrasting two recent studies, one tracking the geographical location of dollar bills \cite{brockmann}, the other that of mobile cell phones \cite{gonzalez}. Trips introduce two characteristic time scales; the time between trips, $θ$, and the duration of each trip, $τ$, and relocations introduces a third time scale, $T$, for the time between relocations. In practice, $T\sim{\rm years}$, $θ\sim{\rm months}$, and $τ\sim{\rm days}$, so the three time scales are widely separated. Traditionally, studies incorporating human motion assume only a single mode, using a generic rate to account for all types of motion.

physics.soc-ph↗

arXiv2011

Communities and Patterns of Scientific collaboration

This paper investigates the role of homophily and focus constraint in shaping collaborative scientific research. First, homophily structures collaboration when scientists adhere to a norm of exclusivity in selecting similar partners at a higher rate than dissimilar ones. Two dimensions on which similarity between scientists can be assessed are their research specialties and status positions. Second, focus constraint shapes collaboration when connections among scientists depend on opportunities for social contact. Constraint comes in two forms, depending on whether it originates in institutional or geographic space. Institutional constraint refers to the tendency of scientists to select collaborators within rather than across institutional boundaries. Geographic constraint is the principle that, when collaborations span different institutions, they are more likely to involve scientists that are geographically co-located than dispersed. To study homophily and focus constraint, the paper will argue in favour of an idea of collaboration that moves beyond formal co-authorship to include also other forms of informal intellectual exchange that do not translate into the publication of joint work. A community-detection algorithm is applied to the co-authorship network of the scientists that submitted in Business and Management in the 2001 UK RAE. While results only partially support research-based homophily, they indicate that scientists use status positions for discriminating between potential partners by selecting collaborators from institutions with a rating similar to their own. Strong support is provided in favour of institutional and geographic constraints. Scientists tend to forge intra-institutional collaborations; yet, when they seek collaborators outside their own institutions, they tend to select those who are in geographic proximity.

physics.soc-ph↗

arXiv2011

A note on measurement of network vulnerability under random and intentional attacks

In this paper we propose an alternative approach for the assessment of network vulnerability under random and intentional attacks as compared to the results obtained from the "vulnerability function" given by Criado et al. [Criado et al. (Int. J. Comput. Math., 86 (2) (2009), pp. 209-218)]. By using spectral and statistical measurements, we assess robustness as the antonym to vulnerability of complex networks and suggest a tentative ranking for vulnerability, based on the interpretation of quantified network characteristics. We conclude that vulnerability function, derived from the network's degree distribution and its variations only, is not general enough to reflect the lack of robustness due to the specific configurations in graphs with hierarchical or centralized structures. The spectral and statistical metrics, on the other hand, capture different aspects of network topology which provide a more thorough assessment of network vulnerability.

physics.comp-ph↗

arXiv2010

Scopus' SNIP Indicator

Rejoinder to Moed [arXiv:1005.4906]: Our main objection is against developing new indicators which, like some of the older ones (for example, the "crown indicator" of CWTS), do not allow for indicating error because they do not provide a statistics, but are based, in our opinion, on a violation of the order of operations. The claim of validity for the SNIP indicator is hollow because the normalizations are based on field classifications which are not valid. Both problems can perhaps be solved by using fractional counting.

cs.DL↗

arXiv2010

Normalization at the field level: fractional counting of citations

Van Raan et al. (2010; arXiv:1003.2113) have proposed a new indicator (MNCS) for field normalization. Since field normalization is also used in the Leiden Rankings of universities, we elaborate our critique of journal normalization in Opthof & Leydesdorff (2010; arXiv:1002.2769) in this rejoinder concerning field normalization. Fractional citation counting thoroughly solves the issue of normalization for differences in citation behavior among fields. This indicator can also be used to obtain a normalized impact factor.

cs.DL↗

arXiv2010

Wealth Distributions in Asset Exchange Models

How do individuals accumulate wealth as they interact economically? We outline the consequences of a simple microscopic model in which repeated pairwise exchanges of assets between individuals build the wealth distribution of a population. This distribution is determined for generic exchange rules --- transactions that involve a fixed amount or a fixed fraction of individual wealth, as well as random or greedy exchanges. In greedy multiplicative exchange, a continuously evolving power law wealth distribution arises, a feature that qualitatively mimics empirical observations.

physics.soc-ph↗

arXiv2012

Taxonomies of Networks

The study of networks has grown into a substantial interdisciplinary endeavour that encompasses myriad disciplines in the natural, social, and information sciences. Here we introduce a framework for constructing taxonomies of networks based on their structural similarities. These networks can arise from any of numerous sources: they can be empirical or synthetic, they can arise from multiple realizations of a single process, empirical or synthetic, or they can represent entirely different systems in different disciplines. Since the mesoscopic properties of networks are hypothesized to be important for network function, we base our comparisons on summaries of network community structures. While we use a specific method for uncovering network communities, much of the introduced framework is independent of that choice. After introducing the framework, we apply it to construct a taxonomy for 746 individual networks and demonstrate that our approach usefully identifies similar networks. We also construct taxonomies within individual categories of networks, and in each case we expose non-trivial structure. For example we create taxonomies for similarity networks constructed from both political voting data and financial data. We also construct network taxonomies to compare the social structures of 100 Facebook networks and the growth structures produced by different types of fungi.

physics.data-an↗

arXiv2011

Evolution of cooperation is a robust outcome in the prisoner's dilemma on dynamic networks

Dynamics of evolutionary games strongly depend on underlying networks. We study the coevolutionary prisoner's dilemma in which players change their local networks as well as strategies (i.e., cooperate or defect). This topic has been increasingly explored by many researchers. On the basis of active linking dynamics [J. M. Pacheco et al., J. Theor. Biol. 243, 437 (2006), J. M. Pacheco et al., Phys. Rev. Lett. 97, 258103 (2006)], we show that cooperation is enhanced fairly robustly. In particular, cooperation evolves when the payoff of the player is normalized by the number of neighbors; this is not the case in the evolutionary prisoner's dilemma on static networks.

physics.soc-ph↗

arXiv2010

Kinetic exchange models for social opinion formation

We propose a minimal model for the collective dynamics of opinion formation in the society, by modifying kinetic exchange dynamics studied in the context of income, money or wealth distributions in a society. This model has an intriguing spontaneous symmetry breaking transition.

physics.soc-ph↗

arXiv2010

How simple regulations can greatly reduce inequality

Many models of market dynamics make use of the idea of wealth exchanges among economic agents. A simple analogy compares the wealth in a society with the energy in a physical system, and the trade between agents to the energy exchange between molecules during collisions. However, while in physical systems the equipartition of energy is valid, in most exchange models for economic markets the system converges to a very unequal "condensed" state, where one or a few agents concentrate all the wealth of the society and the wide majority of agents shares zero or a very tiny fraction of the wealth. Here we present an exchange model where the goal is not only to avoid condensation but also to reduce the inequality; to carry out this objective the choice of interacting agents is not at random, but follows an extremal dynamics regulated by the wealth of the agent. The wealth of the agent with the minimum capital is changed at random and the difference between the ancient and the new wealth of this poorest agent is taken from other agents, so establishing a regulatory tool for wealth redistribution. We compare different redistribution processes and conclude that a drastic reduction of the inequality can be obtained with very simple regulations.

physics.soc-ph↗

arXiv2010

Distinguishing Fact from Fiction: Pattern Recognition in Texts Using Complex Networks

We establish concrete mathematical criteria to distinguish between different kinds of written storytelling, fictional and non-fictional. Specifically, we constructed a semantic network from both novels and news stories, with $N$ independent words as vertices or nodes, and edges or links allotted to words occurring within $m$ places of a given vertex; we call $m$ the word distance. We then used measures from complex network theory to distinguish between news and fiction, studying the minimal text length needed as well as the optimized word distance $m$. The literature samples were found to be most effectively represented by their corresponding power laws over degree distribution $P(k)$ and clustering coefficient $C(k)$; we also studied the mean geodesic distance, and found all our texts were small-world networks. We observed a natural break-point at $k=\sqrt{N}$ where the power law in the degree distribution changed, leading to separate power law fit for the bulk and the tail of $P(k)$. Our linear discriminant analysis yielded a $73.8 \pm 5.15%$ accuracy for the correct classification of novels and $69.1 \pm 1.22%$ for news stories. We found an optimal word distance of $m=4$ and a minimum text length of 100 to 200 words $N$.

cs.CL↗

arXiv2011

Tailor Based Allocations for Multiple Authorship: a fractional $gh$-index

A quantitative modification to keep the number of published papers invariant under multiple authorship is suggested. In those cases, fractional allocations are attributed to each co-author with a summation equal to one. These allocations are tailored on the basis of each author contribution. It is denoted "Tailor Based Allocations (TBA)" for multiple authorship. Several protocols to TBA are suggested. The choice of a specific TBA may vary from one discipline to another. In addition, TBA is applied to the number of citations of a multiple author paper to have also this number conserved. Each author gets only a specific fraction of the total number of citations according to its fractional paper allocation. The equivalent of the h-index obtained by using TBA is denoted the gh-index. It yields values which differ drastically from those given by the h-index. The gh-index departs also from the `h-index recently proposed by Hirsh to account for multiple authorship. Contrary to the h-index, the gh-index is a function of the total number of citations of each paper. A highly cited paper allows a better allocation for all co-authors while a less cited paper contributes essentially to one or two of the co-authors. The scheme produces a substantial redistribution of the ranking of scientists in terms of quantitative records. A few illustrations are provided.

physics.soc-ph↗