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Growing random networks with fitness

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  • Ergün, G.
  • Rodgers, G.J.
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    Abstract

    Three models of growing random networks with fitness-dependent growth rates are analysed using the rate equations for the distribution of their connectivities. In the first model (A), a network is built by connecting incoming nodes to nodes of connectivity k and random additive fitness η, with rate (k−1)+η. For η>0 we find the connectivity distribution is power law with exponent γ=〈η〉+2. In the second model (B), the network is built by connecting nodes to nodes of connectivity k, random additive fitness η and random multiplicative fitness ζ with rate ζ(k−1)+η. This model also has a power law connectivity distribution, but with an exponent which depends on the multiplicative fitness at each node. In the third model (C), a directed graph is considered and is built by the addition of nodes and the creation of links. A node with fitness (α,β), i incoming links and j outgoing links gains a new incoming link with rate α(i+1), and a new outgoing link with rate β(j+1). The distributions of the number of incoming and outgoing links both scale as power laws, with inverse logarithmic corrections.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0378437101004083
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    Bibliographic Info

    Article provided by Elsevier in its journal Physica A: Statistical Mechanics and its Applications.

    Volume (Year): 303 (2002)
    Issue (Month): 1 ()
    Pages: 261-272

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    Handle: RePEc:eee:phsmap:v:303:y:2002:i:1:p:261-272

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    Web page: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/

    Related research

    Keywords: Growing network; Fitness;

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    Cited by:
    1. Colizza, Vittoria & Flammini, Alessandro & Maritan, Amos & Vespignani, Alessandro, 2005. "Characterization and modeling of protein–protein interaction networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 352(1), pages 1-27.
    2. Andersson, Claes & Hellervik, Alexander & Lindgren, Kristian, 2005. "A spatial network explanation for a hierarchy of urban power laws," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 345(1), pages 227-244.
    3. Claes Andersson & Koen Frenken & Alexander Hellervik, 2005. "A complex network approach to urban growth," Papers in Evolutionary Economic Geography (PEEG) 0505, Utrecht University, Section of Economic Geography, revised Feb 2005.
    4. Santiago, A. & Benito, R.M., 2009. "Local affinity in heterogeneous growing networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(14), pages 2941-2948.
    5. Kii, Masanobu & Akimoto, Keigo & Doi, Kenji, 2012. "Random-growth urban model with geographical fitness," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(23), pages 5960-5970.
    6. Zheng, Xiaolong & Zeng, Daniel & Li, Huiqian & Wang, Feiyue, 2008. "Analyzing open-source software systems as complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(24), pages 6190-6200.
    7. Santiago, A. & Benito, R.M., 2008. "Connectivity degrees in the threshold preferential attachment model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(10), pages 2365-2376.

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