IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v391y2012i8p2752-2763.html
   My bibliography  Save this article

Ordered community structure in networks

Author

Listed:
  • Gregory, Steve

Abstract

Community structure in networks is often a consequence of homophily, or assortative mixing, based on some attribute of the vertices. For example, researchers may be grouped into communities corresponding to their research topic. This is possible if vertex attributes have unordered discrete values, but many networks exhibit assortative mixing by some ordered (discrete or continuous) attribute, such as age or geographical location. In such cases, the identification of discrete communities may be difficult or impossible. We consider how the notion of community structure can be generalized to networks that have assortative mixing by ordered attributes. We propose a method of generating synthetic networks with ordered communities and investigate the effect of ordered community structure on the spread of infectious diseases. We also show that current community detection algorithms fail to recover community structure in ordered networks, and evaluate an alternative method using a layout algorithm to recover the ordering.

Suggested Citation

  • Gregory, Steve, 2012. "Ordered community structure in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(8), pages 2752-2763.
    • Handle: RePEc:eee:phsmap:v:391:y:2012:i:8:p:2752-2763
    DOI: 10.1016/j.physa.2011.12.025
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437111009411
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2011.12.025?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Filippo Radicchi, 2011. "Who Is the Best Player Ever? A Complex Network Analysis of the History of Professional Tennis," PLOS ONE, Public Library of Science, vol. 6(2), pages 1-7, February.
    2. Marcel Salathé & James H Jones, 2010. "Dynamics and Control of Diseases in Networks with Community Structure," PLOS Computational Biology, Public Library of Science, vol. 6(4), pages 1-11, April.
    3. Aral, S.O. & Hughes, J.P. & Stoner, B. & Whittington, W. & Handsfield, H.H. & Anderson, R.M. & Holmes, K.K., 1999. "Sexual mixing patterns in the spread of gonococcal and chlamydial infections," American Journal of Public Health, American Public Health Association, vol. 89(6), pages 825-833.
    4. Ciro Cattuto & Wouter Van den Broeck & Alain Barrat & Vittoria Colizza & Jean-François Pinton & Alessandro Vespignani, 2010. "Dynamics of Person-to-Person Interactions from Distributed RFID Sensor Networks," PLOS ONE, Public Library of Science, vol. 5(7), pages 1-9, July.
    5. Andrea Lancichinetti & Filippo Radicchi & José J Ramasco & Santo Fortunato, 2011. "Finding Statistically Significant Communities in Networks," PLOS ONE, Public Library of Science, vol. 6(4), pages 1-18, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wu, Jianshe & Li, Xiaoxiao & Jiao, Licheng & Wang, Xiaohua & Sun, Bo, 2013. "Minimum spanning trees for community detection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2265-2277.
    2. Telcs, András & Csernai, Márton & Gulyás, András, 2013. "Load balanced diffusive capture process on homophilic scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(3), pages 510-519.
    3. Wu, Jianshe & Hou, Yunting & Jiao, Yang & Li, Yong & Li, Xiaoxiao & Jiao, Licheng, 2015. "Density shrinking algorithm for community detection with path based similarity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 433(C), pages 218-228.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Eugenio Valdano & Chiara Poletto & Armando Giovannini & Diana Palma & Lara Savini & Vittoria Colizza, 2015. "Predicting Epidemic Risk from Past Temporal Contact Data," PLOS Computational Biology, Public Library of Science, vol. 11(3), pages 1-19, March.
    2. Benjamin Blonder & Anna Dornhaus, 2011. "Time-Ordered Networks Reveal Limitations to Information Flow in Ant Colonies," PLOS ONE, Public Library of Science, vol. 6(5), pages 1-8, May.
    3. Shang, Jiaxing & Liu, Lianchen & Li, Xin & Xie, Feng & Wu, Cheng, 2015. "Epidemic spreading on complex networks with overlapping and non-overlapping community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 171-182.
    4. Taghavian, Fatemeh & Salehi, Mostafa & Teimouri, Mehdi, 2017. "A local immunization strategy for networks with overlapping community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 148-156.
    5. Thomas Obadia & Romain Silhol & Lulla Opatowski & Laura Temime & Judith Legrand & Anne C M Thiébaut & Jean-Louis Herrmann & Éric Fleury & Didier Guillemot & Pierre-Yves Boëlle & on behalf of the I-Bir, 2015. "Detailed Contact Data and the Dissemination of Staphylococcus aureus in Hospitals," PLOS Computational Biology, Public Library of Science, vol. 11(3), pages 1-16, March.
    6. Wu, Jianshe & Zhang, Long & Li, Yong & Jiao, Yang, 2016. "Partition signed social networks via clustering dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 568-582.
    7. Wei Zhong, 2017. "Simulating influenza pandemic dynamics with public risk communication and individual responsive behavior," Computational and Mathematical Organization Theory, Springer, vol. 23(4), pages 475-495, December.
    8. De Martino, Giuseppe & Spina, Serena, 2015. "Exploiting the time-dynamics of news diffusion on the Internet through a generalized Susceptible–Infected model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 634-644.
    9. Kobayashi, Teruyoshi & Takaguchi, Taro, 2018. "Identifying relationship lending in the interbank market: A network approach," Journal of Banking & Finance, Elsevier, vol. 97(C), pages 20-36.
    10. Chen, Dandan & Zheng, Muhua & Zhao, Ming & Zhang, Yu, 2018. "A dynamic vaccination strategy to suppress the recurrent epidemic outbreaks," Chaos, Solitons & Fractals, Elsevier, vol. 113(C), pages 108-114.
    11. Chang, Y.F. & Han, S.K. & Wang, X.D., 2018. "The way to uncover community structure with core and diversity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 111-119.
    12. Guillermo Durán, 2021. "Sports scheduling and other topics in sports analytics: a survey with special reference to Latin America," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(1), pages 125-155, April.
    13. Bowen Yan & Steve Gregory, 2013. "Identifying Communities and Key Vertices by Reconstructing Networks from Samples," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-14, April.
    14. Fabio Caccioli & Paolo Barucca & Teruyoshi Kobayashi, 2018. "Network models of financial systemic risk: a review," Journal of Computational Social Science, Springer, vol. 1(1), pages 81-114, January.
    15. Wu, Zhihao & Lin, Youfang & Wan, Huaiyu & Tian, Shengfeng & Hu, Keyun, 2012. "Efficient overlapping community detection in huge real-world networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(7), pages 2475-2490.
    16. Zhou, Bin & Yan, Xiao-Yong & Xu, Xiao-Ke & Xu, Xiao-Ting & Wang, Nianxin, 2018. "Evolutionary of online social networks driven by pareto wealth distribution and bidirectional preferential attachment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 427-434.
    17. Stefano Guarino & Enrico Mastrostefano & Massimo Bernaschi & Alessandro Celestini & Marco Cianfriglia & Davide Torre & Lena Rebecca Zastrow, 2021. "Inferring Urban Social Networks from Publicly Available Data," Future Internet, MDPI, vol. 13(5), pages 1-45, April.
    18. Saxena, Chandni & Doja, M.N. & Ahmad, Tanvir, 2018. "Group based centrality for immunization of complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 35-47.
    19. Ghahramani, Ali & Pantelic, Jovan & Lindberg, Casey & Mehl, Matthias & Srinivasan, Karthik & Gilligan, Brian & Arens, Edward, 2018. "Learning occupants’ workplace interactions from wearable and stationary ambient sensing systems," Applied Energy, Elsevier, vol. 230(C), pages 42-51.
    20. Hanjue Xia & Johannes Horn & Monika J Piotrowska & Konrad Sakowski & André Karch & Hannan Tahir & Mirjam Kretzschmar & Rafael Mikolajczyk, 2021. "Effects of incomplete inter-hospital network data on the assessment of transmission dynamics of hospital-acquired infections," PLOS Computational Biology, Public Library of Science, vol. 17(5), pages 1-18, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:391:y:2012:i:8:p:2752-2763. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.