IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v463y2016icp485-492.html
   My bibliography  Save this article

Reconstruction of social group networks from friendship networks using a tag-based model

Author

Listed:
  • Guan, Yuan-Pan
  • You, Zhi-Qiang
  • Han, Xiao-Pu

Abstract

Social group is a type of mesoscopic structure that connects human individuals in microscopic level and the global structure of society. In this paper, we propose a tag-based model considering that social groups expand along the edge that connects two neighbors with a similar tag of interest. The model runs on a real-world friendship network, and its simulation results show that various properties of simulated group network can well fit the empirical analysis on real-world social groups, indicating that the model catches the major mechanism driving the evolution of social groups and successfully reconstructs the social group network from a friendship network and throws light on digging of relationships between social functional organizations.

Suggested Citation

  • Guan, Yuan-Pan & You, Zhi-Qiang & Han, Xiao-Pu, 2016. "Reconstruction of social group networks from friendship networks using a tag-based model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 485-492.
    • Handle: RePEc:eee:phsmap:v:463:y:2016:i:c:p:485-492
    DOI: 10.1016/j.physa.2016.07.020
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437116304514
    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.2016.07.020?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. Wu, Xiaoyan & Liu, Zonghua, 2008. "How community structure influences epidemic spread in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(2), pages 623-630.
    2. Gergely Palla & Imre Derényi & Illés Farkas & Tamás Vicsek, 2005. "Uncovering the overlapping community structure of complex networks in nature and society," Nature, Nature, vol. 435(7043), pages 814-818, June.
    3. Chen, Jiancong & Zhang, Huiling & Guan, Zhi-Hong & Li, Tao, 2012. "Epidemic spreading on networks with overlapping community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1848-1854.
    4. Toivonen, Riitta & Onnela, Jukka-Pekka & Saramäki, Jari & Hyvönen, Jörkki & Kaski, Kimmo, 2006. "A model for social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 371(2), pages 851-860.
    5. Miao, Lili & Zhang, Qian-Ming & Nie, Da-Cheng & Cai, Shi-Min, 2015. "Whether information network supplements friendship network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 301-306.
    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. Xu, Xiao-Ting & Wang, Nianxin & Bian, Jun & Zhou, Bin, 2019. "Understanding the diversity on power-law-like degree distribution in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 576-581.

    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. Shang, Jiaxing & Liu, Lianchen & Li, Xin & Xie, Feng & Wu, Cheng, 2016. "Targeted revision: A learning-based approach for incremental community detection in dynamic networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 70-85.
    2. 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.
    3. Zhang, Ruixia & Li, Deyu, 2017. "Rumor propagation on networks with community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 375-385.
    4. Mattia G. Bergomi & Massimo Ferri & Pietro Vertechi & Lorenzo Zuffi, 2021. "Beyond Topological Persistence: Starting from Networks," Mathematics, MDPI, vol. 9(23), pages 1-15, November.
    5. Han, Dun & Sun, Mei & Li, Dandan, 2015. "Epidemic process on activity-driven modular networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 354-362.
    6. Eustace, Justine & Wang, Xingyuan & Cui, Yaozu, 2015. "Community detection using local neighborhood in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 665-677.
    7. Xiao‐Bing Hu & Hang Li & XiaoMei Guo & Pieter H. A. J. M. van Gelder & Peijun Shi, 2019. "Spatial Vulnerability of Network Systems under Spatially Local Hazards," Risk Analysis, John Wiley & Sons, vol. 39(1), pages 162-179, January.
    8. Jorge Peña & Yannick Rochat, 2012. "Bipartite Graphs as Models of Population Structures in Evolutionary Multiplayer Games," PLOS ONE, Public Library of Science, vol. 7(9), pages 1-13, September.
    9. Pirvu Daniela & Barbuceanu Mircea, 2016. "Recent Contributions Of The Statistical Physics In The Research Of Banking, Stock Exchange And Foreign Exchange Markets," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 2, pages 85-92, April.
    10. Daniel M. Ringel & Bernd Skiera, 2016. "Visualizing Asymmetric Competition Among More Than 1,000 Products Using Big Search Data," Marketing Science, INFORMS, vol. 35(3), pages 511-534, May.
    11. Yu, Shuo & Alqahtani, Fayez & Tolba, Amr & Lee, Ivan & Jia, Tao & Xia, Feng, 2022. "Collaborative Team Recognition: A Core Plus Extension Structure," Journal of Informetrics, Elsevier, vol. 16(4).
    12. Roth, Camille, 2007. "Empiricism for descriptive social network models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 378(1), pages 53-58.
    13. Johansson, Tobias, 2017. "Gossip spread in social network Models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 126-134.
    14. Ying Song & Zhiwen Zheng & Yunmei Shi & Bo Wang, 2023. "GLOD: The Local Greedy Expansion Method for Overlapping Community Detection in Dynamic Provenance Networks," Mathematics, MDPI, vol. 11(15), pages 1-16, July.
    15. Shiau, Wen-Lung & Dwivedi, Yogesh K. & Yang, Han Suan, 2017. "Co-citation and cluster analyses of extant literature on social networks," International Journal of Information Management, Elsevier, vol. 37(5), pages 390-399.
    16. Zhang, Zhiwei & Wang, Zhenyu, 2015. "Mining overlapping and hierarchical communities in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 25-33.
    17. J. Sylvan Katz & Guillermo Armando Ronda-Pupo, 2019. "Cooperation, scale-invariance and complex innovation systems: a generalization," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(2), pages 1045-1065, November.
    18. Postigo-Boix, Marcos & Melús-Moreno, José L., 2018. "A social model based on customers’ profiles for analyzing the churning process in the mobile market of data plans," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 571-592.
    19. Masa Tsuchiya & Vincent Piras & Alessandro Giuliani & Masaru Tomita & Kumar Selvarajoo, 2010. "Collective Dynamics of Specific Gene Ensembles Crucial for Neutrophil Differentiation: The Existence of Genome Vehicles Revealed," PLOS ONE, Public Library of Science, vol. 5(8), pages 1-10, August.
    20. 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.

    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:463:y:2016:i:c:p:485-492. 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.