Scale-free behavior of networks with the copresence of preferential and uniform attachment rules
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TLDR
This work introduces and study a model which takes into account two different attachment rules: a preferential attachment mechanism that stresses the rich get richer system and a uniform choice for the most recent nodes, i.e. the nodes belonging to a window of size w to the left of the last born node.About:
This article is published in Physica D: Nonlinear Phenomena.The article was published on 2018-05-15 and is currently open access. It has received 29 citations till now. The article focuses on the topics: Degree distribution & Preferential attachment.read more
Citations
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Scale-free networks are rare
Anna D. Broido,Aaron Clauset +1 more
TL;DR: A severe test of their empirical prevalence using state-of-the-art statistical tools applied to nearly 1000 social, biological, technological, transportation, and information networks finds robust evidence that strongly scale-free structure is empirically rare, while for most networks, log-normal distributions fit the data as well or better than power laws.
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Scale-free networks are rare
Anna D. Broido,Aaron Clauset +1 more
TL;DR: In this article, the authors test the universality of scale-free structure by applying state-of-the-art statistical tools to a large corpus of nearly 1000 network data sets drawn from social, biological, technological, and informational sources.
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On discrete-time semi-Markov processes
TL;DR: In this paper, a class of discrete-time semi-Markov chains which can be constructed as time-changed Markov chains and the related governing convolution type equations are obtained.
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Generating Graphs by Creating Associative and Random Links Between Existing Nodes
Muhammad Irfan Yousuf,Suhyun Kim +1 more
TL;DR: This paper proposes a new generative model for generating realistic networks that is a blend of three key ideas namely preferential attachment, associativity of social links and randomness in real networks and gives both qualitative and quantitative results for clarity.
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Network Features of the EU Carbon Trade System: An Evolutionary Perspective
TL;DR: By modeling the heterogeneity of the carbon trading network, it is found that the trading relationships between firms obey a broken power law model, which consists of two power law models.
References
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Handbook of Mathematical Functions
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Emergence of Scaling in Random Networks
TL;DR: A model based on these two ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.
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