IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v433y2015icp259-267.html
   My bibliography  Save this article

Topological evolution of virtual social networks by modeling social activities

Author

Listed:
  • Sun, Xin
  • Dong, Junyu
  • Tang, Ruichun
  • Xu, Mantao
  • Qi, Lin
  • Cai, Yang

Abstract

With the development of Internet and wireless communication, virtual social networks are becoming increasingly important in the formation of nowadays’ social communities. Topological evolution model is foundational and critical for social network related researches. Up to present most of the related research experiments are carried out on artificial networks, however, a study of incorporating the actual social activities into the network topology model is ignored. This paper first formalizes two mathematical abstract concepts of hobbies search and friend recommendation to model the social actions people exhibit. Then a social activities based topology evolution simulation model is developed to satisfy some well-known properties that have been discovered in real-world social networks. Empirical results show that the proposed topology evolution model has embraced several key network topological properties of concern, which can be envisioned as signatures of real social networks.

Suggested Citation

  • Sun, Xin & Dong, Junyu & Tang, Ruichun & Xu, Mantao & Qi, Lin & Cai, Yang, 2015. "Topological evolution of virtual social networks by modeling social activities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 433(C), pages 259-267.
    • Handle: RePEc:eee:phsmap:v:433:y:2015:i:c:p:259-267
    DOI: 10.1016/j.physa.2015.03.069
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437115003313
    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.2015.03.069?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. Wei, Dong & Zhou, Tao & Cimini, Giulio & Wu, Pei & Liu, Weiping & Zhang, Yi-Cheng, 2011. "Effective mechanism for social recommendation of news," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(11), pages 2117-2126.
    2. Yan, Qiang & Wu, Lianren & Zheng, Lan, 2013. "Social network based microblog user behavior analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(7), pages 1712-1723.
    3. Bu, Zhan & Xia, Zhengyou & Wang, Jiandong & Zhang, Chengcui, 2013. "A last updating evolution model for online social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2240-2247.
    4. Traud, Amanda L. & Mucha, Peter J. & Porter, Mason A., 2012. "Social structure of Facebook networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(16), pages 4165-4180.
    5. Freeman, Mark & McVittie, James & Sivak, Iryna & Wu, Jianhong, 2014. "Viral information propagation in the Digg online social network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 87-94.
    6. Liu, Qipeng & Wang, Xiaofan, 2013. "Social learning with bounded confidence and heterogeneous agents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(10), pages 2368-2374.
    7. Hai-Bo Hu & Lin Wang, 2005. "The Gini Coefficient'S Application To General Complex Networks," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 8(01), pages 159-167.
    8. Hu, Haibo & Han, Dingyi & Wang, Xiaofan, 2010. "Individual popularity and activity in online social systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(5), pages 1065-1070.
    Full references (including those not matched with items on IDEAS)

    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. Yuan, Wei-Guo & Liu, Yun, 2015. "A mixing evolution model for bidirectional microblog user networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 167-179.
    2. Fan, Rui & Xu, Ke & Zhao, Jichang, 2018. "An agent-based model for emotion contagion and competition in online social media," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 495(C), pages 245-259.
    3. Liu, Xiao Fan & Tse, Chi Kong, 2014. "Impact of degree mixing pattern on consensus formation in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 407(C), pages 1-6.
    4. Xin Xu & Yang Lu & Yupeng Zhou & Zhiguo Fu & Yanjie Fu & Minghao Yin, 2021. "An Information-Explainable Random Walk Based Unsupervised Network Representation Learning Framework on Node Classification Tasks," Mathematics, MDPI, vol. 9(15), pages 1-14, July.
    5. Jiashun Jin & Zheng Tracy Ke & Shengming Luo, 2022. "Improvements on SCORE, Especially for Weak Signals," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(1), pages 127-162, June.
    6. Han, Kevin & Basse, Guillaume & Bojinov, Iavor, 2024. "Population interference in panel experiments," Journal of Econometrics, Elsevier, vol. 238(1).
    7. Diao, Su-Meng & Liu, Yun & Zeng, Qing-An & Luo, Gui-Xun & Xiong, Fei, 2014. "A novel opinion dynamics model based on expanded observation ranges and individuals’ social influences in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 220-228.
    8. Saxena, Rakhi & Kaur, Sharanjit & Bhatnagar, Vasudha, 2019. "Identifying similar networks using structural hierarchy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    9. Luca Braghieri & Ro'ee Levy & Alexey Makarin, 2022. "Social Media and Mental Health," American Economic Review, American Economic Association, vol. 112(11), pages 3660-3693, November.
    10. Su, Qiang & Huang, Jiajia & Zhao, Xiande, 2015. "An information propagation model considering incomplete reading behavior in microblog," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 55-63.
    11. Zhao, Danling & Sun, Jianbin & Tan, Yuejin & Wu, Jianhong & Dou, Yajie, 2018. "An extended SEIR model considering homepage effect for the information propagation of online social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 1019-1031.
    12. Ma, Shujie & Su, Liangjun & Zhang, Yichong, 2020. "Detecting Latent Communities in Network Formation Models," Economics and Statistics Working Papers 12-2020, Singapore Management University, School of Economics.
    13. Ciotti, Valerio & Bianconi, Ginestra & Capocci, Andrea & Colaiori, Francesca & Panzarasa, Pietro, 2015. "Degree correlations in signed social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 422(C), pages 25-39.
    14. Wang, Mingyan & Zeng, An & Cui, Xiaohua, 2022. "Collective user switching behavior reveals the influence of TV channels and their hidden community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    15. Jason Jung, 2014. "Understanding information propagation on online social tagging systems: a case study on Flickr," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(2), pages 745-754, March.
    16. Ping Jiang & Xiangbin Yan, 2019. "A quantitative model for the spread of online information," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(4), pages 1981-2001, July.
    17. Lianren Wu & Jinjie Li & Jiayin Qi & Deli Kong & Xu Li, 2021. "The Role of Opinion Leaders in the Sustainable Development of Corporate-Led Consumer Advice Networks: Evidence from a Chinese Travel Content Community," Sustainability, MDPI, vol. 13(19), pages 1-20, October.
    18. Yi-Shan Sung & Dashun Wang & Soundar Kumara, 0. "Uncovering the effect of dominant attributes on community topology: A case of facebook networks," Information Systems Frontiers, Springer, vol. 0, pages 1-12.
    19. Karimi, Fariba & Ramenzoni, Verónica C. & Holme, Petter, 2014. "Structural differences between open and direct communication in an online community," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 263-273.
    20. Yi, Chengqi & Bao, Yuanyuan & Xue, Yibo, 2016. "Mining the key predictors for event outbreaks in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 247-260.

    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:433:y:2015:i:c:p:259-267. 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.