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336
Crossover from scalefree to spatial networks
, 2003
"... PACS. 89.75.Fb – Structures and organization in complex systems. PACS. 89.75.Hc – Networks and genealogical trees. PACS. 05.40.a – Fluctuation phenomena, random processes, noise, and Brownian motion. Abstract. – In many networks such as transportation or communication networks, distance is certainl ..."
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Cited by 21 (0 self)
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finite “interaction range”. We study the crossover from the scalefree to the “spatial ” network as the interaction range decreases and we propose scaling forms for different quantities describing the network. In particular, when the distance effect is important i) the connectivity distribution has a cut
Exactly solvable scalefree network models
, 2004
"... We study a deterministic scalefree network recently proposed by Barabási, Ravasz and Vicsek. We find that there are two types of nodes: the hub and rim nodes, which form a bipartite structure of the network. We first derive the exact numbers P(k) of nodes with degree k for the hub and rim nodes in ..."
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Cited by 2 (0 self)
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in each generation of the network, respectively. Using this, we obtain the exact exponents of the distribution function P(k) of nodes with k degree in the asymptotic limit of k → ∞. We show that the degree distribution for the hub nodes exhibits the scalefree nature, P(k) ∝ k −γ with γ = ln 3/ln 2 = 1
Deanonymizing Scalefree Social Networks by Percolation Graph Matching
"... AbstractWe address the problem of social network deanonymization when relationships between people are described by scalefree graphs. In particular, we propose a rigorous, asymptotic mathematical analysis of the network deanonymization problem while capturing the impact of powerlaw node degree ..."
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AbstractWe address the problem of social network deanonymization when relationships between people are described by scalefree graphs. In particular, we propose a rigorous, asymptotic mathematical analysis of the network deanonymization problem while capturing the impact of powerlaw node degree
Microscopic Evolution of Social Networks
, 2008
"... We present a detailed study of network evolution by analyzing four large online social networks with full temporal information about node and edge arrivals. For the first time at such a large scale, we study individual node arrival and edge creation processes that collectively lead to macroscopic pr ..."
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Cited by 206 (10 self)
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triangleclosing model free of any parameters. We show analytically that the combination of the gap distribution with the node lifetime leads to a power law outdegree distribution that accurately reflects the true network in all four cases. Finally, we give model parameter settings that allow automatic
Emergence of ScaleFree CloseKnit Friendship Structure in Online Social Networks
"... Although the structural properties of online social networks have attracted much attention, the properties of the closeknit friendship structures remain an important question. Here, we mainly focus on how these mesoscale structures are affected by the local and global structural properties. Analyzi ..."
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. Analyzing the data of four largescale online social networks reveals several common structural properties. It is found that not only the local structures given by the indegree, outdegree, and reciprocal degree distributions follow a similar scaling behavior, the mesoscale structures represented
Selfdetermination and persistence in a reallife setting: Toward a motivational model of high school dropout.
 Journal of Personality and Social Psychology,
, 1997
"... The purpose of this study was to propose and test a motivational model of high school dropout. The model posits that teachers, parents, and the school administration's behaviors toward students influence students' perceptions of competence and autonomy. The less autonomy supportive the so ..."
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Cited by 183 (19 self)
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or who desire a career that requires a college degree intend to pursue their schooling. For a substantial portion of students, however, selfdetermined motivation toward school has become so low (i.e., they have developed low levels of intrinsic motivation and identified regulation but high levels
Whom You Know Matters: Venture Capital Networks and Investment Performance,
 Journal of Finance
, 2007
"... Abstract Many financial markets are characterized by strong relationships and networks, rather than arm'slength, spotmarket transactions. We examine the performance consequences of this organizational choice in the context of relationships established when VCs syndicate portfolio company inv ..."
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Cited by 138 (8 self)
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centrality measure by dividing by the maximum possible degree in an nactor network (i.e., n1). While we normalize the centrality measures used in the empirical analysis, we note that all our results are robust to using nonnormalized network centrality measures instead. 8 B. Closeness While degree counts
Materials for an exploratory theory of the network society.
 The British Journal of Sociology
, 2000
"... ABSTRACT This article aims at proposing some elements for a grounded theor y of the network society. The network society is the social structure characteristic of the Information Age, as tentatively identi ed by empirical, crosscultural investigation. It permeates most societies in the world, in v ..."
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Cited by 122 (0 self)
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, but from their ability to be trusted by the network with an extrashare of information. In this sense, the main nodes are not centres, but switchers, following a networking logic rather than a command logic, in their function visàvis the overall structure. Networks, as social forms, are valuefree
The Duality of Maximum Delay and Maximum Backlog
"... Abstract—In this paper, we will establish a duality between maximum delay and maximum backlog in a single queue network. Minplus algebra will be employed to devise the duality. In minplus algebra, the maximum backlog is represented by the scalar projection of accumulated input traffic curve onto ..."
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. In a matched queue, the maximum delay and the maximum backlog are identical and are equal to the leftnorm of input process. I. introduction Worstcase qualityofservice (QoS) provisioning has been the focus of recent research in highspeed networking [1] — [7]. QoS is usually indicated
On a 2parameter class of scale free random graphs
 Acta Math. Hungar
"... Consider the following modification of the Barabási–Albert random graph. At every step a new vertex is added to the graph. It is connected to the old vertices randomly, with probabilities proportional to the degree of the other vertex, and independently of each other. We show that the proportion of ..."
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Cited by 10 (1 self)
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of vertices of degree k decreases at the rate of k−3. Furthermore, we prove a strong law of large numbers for the maximum degree. 1. The model The examination of complex networks, such as the World Wide Web, led to the emerging role of random networks. Barabási and Albert [1] pointed out that many complex
Results 1  10
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336