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Modelling and Simulation of an Infection Disease in Social Networks

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Book cover Computational Collective Intelligence. Technologies and Applications (ICCCI 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6922))

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Abstract

The paper focuses its attention on a software project that takes advantage of pioneering sociological theories, graph & network theory, and the state-of-the-art in software technologies. Its very purpose, of particularly high importance nowadays, is to counter infectious diseases. The paper refers to research of Complex Networks displaying the, so called, Scale Free and Small World features, which make them accurate models of Social Networks.

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References

  1. Erdös, P., Rényi, A.: On random graphs, Publ. Math. Debrecen. 6, 290–297 (1959)

    MathSciNet  MATH  Google Scholar 

  2. Watts, D.J., Strogatz, S.H.: Collective dynamics of small-world” networks. Nature 393, 440–442 (1998)

    Article  MATH  Google Scholar 

  3. Barabasi, A.L., Reka, A.: Emergency of Scaling in Random Networks. Science 286, 509–512 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  4. Barabasi, A.L., Reka, A.: Statistical mechanics of complex networks. Review of Modern Physics 74, 47–97 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  5. Watts, D.J.: Small Worlds: The Dynamics of Networks Between Order and Randomness. Princeton University Press, Princeton (1999)

    MATH  Google Scholar 

  6. Harary, F., Hage, P.: Eccentricity and centrality in networks. Social Networks 17, 57–63 (1995)

    Article  Google Scholar 

  7. Kasprzyk, R.: The vaccination against epidemic spreading in Complex Networks, ISSN 1508-4183, Biuletyn ISI, Nr 3/2009, Warszawa, pp. 1508–4183 (2009)

    Google Scholar 

  8. Brandes, U., Kenis, P., Raab, J.: Explanation Through Network Visualization. Methodology 2(1), 16–23 (2006)

    Article  Google Scholar 

  9. Pastor-Satorras, R., Vespignani, A.: Epidemic Spreading in Scale-Free Networks. PRL 86(14), 3200 (2001)

    Article  Google Scholar 

  10. Crucitti, P., Latora, V., Marchiori, M., Rapisarda, A.: Error and attack tolerance of complex networks. Physica A 340, 388–394 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  11. Wuchty, S., Stadler, P.F.: Centers of complex networks. Journal of Theoretical Biology 222, 45–53 (2003)

    Article  MathSciNet  Google Scholar 

  12. Barabási, A.L., Albert, R.: Topology of Evolving Networks: Local Events and Universality. PRL 85(24), 5234 (2000)

    Article  Google Scholar 

  13. Cohen, R., Havlin, S., ben-Avraham, D.: Efficient Immunization Strategies for Computer Networks and Population. PRL 24, 247901–247901 (2003)

    Article  Google Scholar 

  14. Madar, N., Kalisky, T., Cohen, R., ben-Avraham, D., Havlin, S.: Immunization and epidemic dynamics in complex networks. Eur. Phys. J. B 38, 269–276 (2004)

    Article  Google Scholar 

  15. Najgebauer, A., Pierzchała, D., Kasprzyk, R.: A distributed multi-level system for monitoring and simulation of epidemics. In: Brebbia, C.A. (ed.) Risk Analysis VII and Brownfields V, pp. 583-596. WITPress (2010) ISBN 978-1-84564-472-7

    Google Scholar 

  16. Kasprzyk, R., Najgebauer, A., Pierzchała, D.: Creative Application to Remedy Epidemics. In: Brebbia, C.A. (ed.) Risk Analysis VII and Brownfields V, pp. 545–562. WIT Press (2010) ISBN: 978-1-84564-472-7

    Google Scholar 

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© 2011 Springer-Verlag Berlin Heidelberg

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Kasprzyk, R., Najgebauer, A., Pierzchała, D. (2011). Modelling and Simulation of an Infection Disease in Social Networks. In: Jędrzejowicz, P., Nguyen, N.T., Hoang, K. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2011. Lecture Notes in Computer Science(), vol 6922. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23935-9_38

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  • DOI: https://doi.org/10.1007/978-3-642-23935-9_38

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23934-2

  • Online ISBN: 978-3-642-23935-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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