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Reconstructing Topological Properties of Complex Networks Using the Fitness Model

  • Giulio Cimini
  • Tiziano Squartini
  • Nicolò Musmeci
  • Michelangelo Puliga
  • Andrea Gabrielli
  • Diego Garlaschelli
  • Stefano Battiston
  • Guido Caldarelli
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8852)

Abstract

A major problem in the study of complex socioeconomic systems is represented by privacy issues—that can put severe limitations on the amount of accessible information, forcing to build models on the basis of incomplete knowledge. In this paper we investigate a novel method to reconstruct global topological properties of a complex network starting from limited information. This method uses the knowledge of an intrinsic property of the nodes (indicated as fitness), and the number of connections of only a limited subset of nodes, in order to generate an ensemble of exponential random graphs that are representative of the real systems and that can be used to estimate its topological properties. Here we focus in particular on reconstructing the most basic properties that are commonly used to describe a network: density of links, assortativity, clustering. We test the method on both benchmark synthetic networks and real economic and financial systems, finding a remarkable robustness with respect to the number of nodes used for calibration. The method thus represents a valuable tool for gaining insights on privacy-protected systems.

Keywords

Complex networks Network reconstruction Exponential random graphs Fitness model 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Giulio Cimini
    • 1
  • Tiziano Squartini
    • 1
  • Nicolò Musmeci
    • 2
  • Michelangelo Puliga
    • 3
  • Andrea Gabrielli
    • 1
    • 3
  • Diego Garlaschelli
    • 4
  • Stefano Battiston
    • 5
  • Guido Caldarelli
    • 3
  1. 1.Institute for Complex Systems (ISC-CNR) UoS “Sapienza”University of RomeRomeItaly
  2. 2.King’s CollegeLondonUK
  3. 3.IMT Institute for Advanced StudiesLuccaItaly
  4. 4.Lorentz Institute for Theoretical PhysicsUniversity of LeidenLeidenThe Netherlands
  5. 5.Department of Banking and FinanceUniversity of ZurichZurichSwitzerland

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