Skip to main content
SpringerLink
Log in
Book cover

International Conference on Complex Networks and their Applications

COMPLEX NETWORKS 2018: Complex Networks and Their Applications VII pp 619–634Cite as

Relating Emerging Network Behaviour to Network Structure

  • Conference paper
  • First Online:

Part of the book series: Studies in Computational Intelligence ((SCI,volume 812))

Abstract

Emerging behaviour of a network is usually considered to be a consequence of the network’s structure, although it may be challenging to find out how this relation between structure and behaviour exactly is. In this paper a number of results are presented on how certain properties of network structure determine network behaviour, in particular what limit behaviour emerges. These network structure properties include in how far states of the network are reachable from a given state, and properties of functions to aggregate multiple impacts on a state.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD   219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Notes

  1. 1.

    http://www.few.vu.nl/~treur/ComplexNetworks18Structure2BehaviourProofs.pdf.

References

  1. Bosse, T., Duell, R., Memon, Z.A., Treur, J., van der Wal, C.N.: Agent-based modeling of emotion contagion in groups. Cogn Comput 7, 111–136 (2015)

    Google Scholar 

  2. Brauer, F., Nohel, J.A.: Qualitative theory of ordinary differential equations. Benjamin (1969)

    Google Scholar 

  3. Castellano, C., Fortunato, S., Loreto, V.: Statistical physics of social dynamics. Rev. Mod. Phys. 81, 591–646 (2009)

    Google Scholar 

  4. Hendrickx, J.M., Tsitsiklis, J.N.: Convergence of type-symmetric and cut-balanced consensus seeking systems. IEEE Trans. Automat. Control 58(1), 214–218 (2013). Extended version: arXiv:1102.2361v2 [cs.SY]

  5. Lotka, A.J. (1956): Elements of Physical Biology. Williams and Wilkins Co. (1924), Dover Publications, 2nd ed.

    Google Scholar 

  6. Pearl, J.: Causality. Cambridge University Press (2000)

    Google Scholar 

  7. Picard, E.: Traité d’Analyse, vol. 1 (1891), vol. 2 (1893)

    Google Scholar 

  8. Poincaré, H.: Mémoire sur les courbes défine par une équation différentielle (On curves defined by differential equations) (1881–1882)

    Google Scholar 

  9. Treur, J.: Verification of temporal-causal network models by mathematical analysis. Vietnam J Comput Sci 3, 207–221 (2016)

    Google Scholar 

  10. Treur, J.: Network-Oriented Modeling: Addressing Complexity of Cognitive, Affective and Social Interactions. Springer Publishers (2016)

    Google Scholar 

  11. Treur, J.: Modelling and Analysis of the Dynamics of Adaptive Temporal-Causal Network Models for Evolving Social Interactions. Computational Social Networks 4, article 4, pp. 1–20 (2017)

    Google Scholar 

  12. Treur, J.: The Ins and Outs of Network-Oriented Modeling: From Biological Networks and Mental Networks to Social Networks and Beyond. Overview paper based on the Keynote Lecture at the 10th International Conference on Computational Collective Intelligence, ICCCI’18. Transactions in Computational Collective Intelligence (2018)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Behavioural Informatics Group, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

    Jan Treur

Authors
  1. Jan Treur
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jan Treur .

Editor information

Editors and Affiliations

  1. Nokia Bell Labs, Cambridge, UK

    Luca Maria Aiello

  2. IUT Lumière, University of Lyon, Bron Cedex, France

    Chantal Cherifi

  3. LE2I UMR CNRS 6306 9, University of Burgundy, Dijon Cedex, France

    Hocine Cherifi

  4. Mathematical Institute, University of Oxford, Oxford, UK

    Renaud Lambiotte

  5. Department of Computer Science and Technology, The Computer Laboratory, University of Cambridge, Cambridge, UK

    Pietro Lió

  6. Center for Complex Networks and Systems Research, School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, USA

    Luis M. Rocha

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Treur, J. (2019). Relating Emerging Network Behaviour to Network Structure. In: Aiello, L., Cherifi, C., Cherifi, H., Lambiotte, R., Lió, P., Rocha, L. (eds) Complex Networks and Their Applications VII. COMPLEX NETWORKS 2018. Studies in Computational Intelligence, vol 812. Springer, Cham. https://doi.org/10.1007/978-3-030-05411-3_50

Download citation

Publish with us

Policies and ethics

Search

Navigation