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Estimation algorithm for counting periodic orbits in complex social networks

Author

Listed:
  • Ibrahim Sorkhoh

    (Kuwait University)

  • Khaled A. Mahdi

    (Kuwait University)

  • Maytham Safar

    (Kuwait University)

Abstract

Complex networks can store information in form of periodic orbits (cycles) existing in the network. This cycle-based approach although computationally intensive, it provided us with useful information about the behavior and connectivity of the network. Social networks in most works are treated like any complex network with minimal sociological features modeled. Hence the cycle distribution will suggest the true capacity of this social network to store information. Counting cycles in complex networks is an NP-hard problem. This work proposed an efficient algorithm based on statistical mechanical based Belief Propagation (BP) algorithm to compute cycles in different complex networks using a phenomenological Gaussian distribution of cycles. The enhanced BP algorithm was applied and tested on different networks and the results showed that our model accurately approximated the cycles distribution of those networks, and that the best accuracy was obtained for the random network. In addition, a clear improvement was achieved in the cycles computation time. In some cases the execution time was reduced by up to 88 % compared to the original BP algorithm.

Suggested Citation

  • Ibrahim Sorkhoh & Khaled A. Mahdi & Maytham Safar, 2013. "Estimation algorithm for counting periodic orbits in complex social networks," Information Systems Frontiers, Springer, vol. 15(2), pages 193-202, April.
    • Handle: RePEc:spr:infosf:v:15:y:2013:i:2:d:10.1007_s10796-012-9366-9
    DOI: 10.1007/s10796-012-9366-9
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    References listed on IDEAS

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    1. Robert Wetzker & Carsten Zimmermann & Christian Bauckhage, 2010. "Detecting Trends in Social Bookmarking Systems: A del.icio.us Endeavor," International Journal of Data Warehousing and Mining (IJDWM), IGI Global, vol. 6(1), pages 38-57, January.
    2. Ralitsa Angelova & Marek Lipczak & Evangelos Milios & Pawel Pralat, 2010. "Investigating the Properties of a Social Bookmarking and Tagging Network," International Journal of Data Warehousing and Mining (IJDWM), IGI Global, vol. 6(1), pages 1-19, January.
    3. Symeon Papadopoulos & Athena Vakali & Ioannis Kompatsiaris, 2010. "The Dynamics of Content Popularity in Social Media," International Journal of Data Warehousing and Mining (IJDWM), IGI Global, vol. 6(1), pages 20-37, January.
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    Cited by:

    1. Gabriele Kotsis & Ismail Khalil, 2013. "Special issue on Semantic Information Management guest editorial," Information Systems Frontiers, Springer, vol. 15(2), pages 151-157, April.
    2. Rezvanian, Alireza & Rahmati, Mohammad & Meybodi, Mohammad Reza, 2014. "Sampling from complex networks using distributed learning automata," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 396(C), pages 224-234.

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