Temporal Networks pp 135-159

Part of the Understanding Complex Systems book series (UCS) | Cite as

Applications of Temporal Graph Metrics to Real-World Networks

  • John Tang
  • Ilias Leontiadis
  • Salvatore Scellato
  • Vincenzo Nicosia
  • Cecilia Mascolo
  • Mirco Musolesi
  • Vito Latora

Abstract

Real world networks exhibit rich temporal information: friends are added and removed over time in online social networks; the seasons dictate the predator-prey relationship in food webs; and the propagation of a virus depends on the network of human contacts throughout the day. Recent studies have demonstrated that static network analysis is perhaps unsuitable in the study of real world network since static paths ignore time order, which, in turn, results in static shortest paths overestimating available links and underestimating their true corresponding lengths. Temporal extensions to centrality and efficiency metrics based on temporal shortest paths have also been proposed. Firstly, we analyse the roles of key individuals of a corporate network ranked according to temporal centrality within the context of a bankruptcy scandal; secondly, we present how such temporal metrics can be used to study the robustness of temporal networks in presence of random errors and intelligent attacks; thirdly, we study containment schemes for mobile phone malware which can spread via short range radio, similar to biological viruses; finally, we study how the temporal network structure of human interactions can be exploited to effectively immunise human populations. Through these applications we demonstrate that temporal metrics provide a more accurate and effective analysis of real-world networks compared to their static counterparts.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • John Tang
    • 1
  • Ilias Leontiadis
    • 1
  • Salvatore Scellato
    • 1
  • Vincenzo Nicosia
    • 1
    • 2
  • Cecilia Mascolo
    • 1
  • Mirco Musolesi
    • 3
  • Vito Latora
    • 2
    • 4
    • 5
  1. 1.Computer LaboratoryUniversity of CambridgeCambridgeUK
  2. 2.Laboratorio sui Sistemi ComplessiScuola Superiore di CataniaCataniaItaly
  3. 3.School of Computer ScienceUniversity of BirminghamBirminghamUK
  4. 4.School of Mathematical SciencesQueen Mary, University of LondonLondonUK
  5. 5.Dipartimento di Fisica e Astronomia and INFNUniversitá di Catania and INFNCataniaItaly

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