IDEAS home Printed from https://ideas.repec.org/a/spr/qualqt/v52y2018i1d10.1007_s11135-016-0465-4.html
   My bibliography  Save this article

Empirical analysis of structural properties, macroscopic and microscopic evolution of various Facebook activity networks

Author

Listed:
  • Ehsan Khadangi

    (Amirkabir University of Technology)

  • Alireza Bagheri

    (Amirkabir University of Technology)

  • Ali Zarean

    (Sharif University of Technology)

Abstract

Recently, some works have been done in studying activity network as a more realistic representation of users’ behavior in online social networks. However, there is a major deficiency of a suitable definition of activity network based on a comprehensive study of various activity networks separately and combined. The main purpose of our research is to understand the differences between users’ behavior by various Facebook activities, so as to claim that these networks should not be blindly composed; neither should the result of analyzing each of them individually be generalized to others. For this purpose, degree distribution, small-world phenomenon, degree correlation, reciprocity, and homophily by different attributes of various activity networks are studied. Then, we study densification and shrinking diameter properties and some structural characteristics of activity networks over time. We also examine microscopic evolution of different activity networks. Ultimately, we conclude that there are some differences between users’ behavior by various Facebook activities but all evolve almost similarly at macroscopic and microscopic levels. However, post network evolves considerably different from other activity networks. Accordingly, a comprehensive definition for activity network is suggested so that the results of analyzing the modeled activity network fit realistic data.

Suggested Citation

  • Ehsan Khadangi & Alireza Bagheri & Ali Zarean, 2018. "Empirical analysis of structural properties, macroscopic and microscopic evolution of various Facebook activity networks," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(1), pages 249-275, January.
    • Handle: RePEc:spr:qualqt:v:52:y:2018:i:1:d:10.1007_s11135-016-0465-4
    DOI: 10.1007/s11135-016-0465-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11135-016-0465-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11135-016-0465-4?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. Crucitti, Paolo & Latora, Vito & Marchiori, Massimo & Rapisarda, Andrea, 2004. "Error and attack tolerance of complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 340(1), pages 388-394.
    2. Giorgio Fagiolo & Tiziano Squartini & Diego Garlaschelli, 2013. "Null models of economic networks: the case of the world trade web," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(1), pages 75-107, April.
    3. Baltar, Fabiola & Brunet Icart, Ignasi, 2012. "Social research 2.0: virtual snowball sampling method using Facebook," Nülan. Deposited Documents 1875, Universidad Nacional de Mar del Plata, Facultad de Ciencias Económicas y Sociales, Centro de Documentación.
    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. Alba Rocio Gutierrez Garzon & Pete Bettinger & Jacek Siry & Bin Mei & Jesse Abrams, 2019. "The Terms Foresters and Planners in the United States Use to Infer Sustainability in Forest Management Plans: A Survey Analysis," Sustainability, MDPI, vol. 12(1), pages 1-20, December.
    2. Quayle, A.P. & Siddiqui, A.S. & Jones, S.J.M., 2006. "Preferential network perturbation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 371(2), pages 823-840.
    3. Fariba Karimi & Matthias Raddant, 2016. "Cascades in Real Interbank Markets," Computational Economics, Springer;Society for Computational Economics, vol. 47(1), pages 49-66, January.
    4. Marco Dueñas & Giorgio Fagiolo, 2013. "Modeling the International-Trade Network: a gravity approach," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(1), pages 155-178, April.
    5. Bellingeri, Michele & Cassi, Davide & Vincenzi, Simone, 2014. "Efficiency of attack strategies on complex model and real-world networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 174-180.
    6. Valentini, Luca & Perugini, Diego & Poli, Giampiero, 2007. "The “small-world” topology of rock fracture networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 377(1), pages 323-328.
    7. Bianca Polenzani & Chiara Riganelli & Andrea Marchini, 2020. "Sustainability Perception of Local Extra Virgin Olive Oil and Consumers’ Attitude: A New Italian Perspective," Sustainability, MDPI, vol. 12(3), pages 1-18, January.
    8. Aybike Ulusan & Ozlem Ergun, 2018. "Restoration of services in disrupted infrastructure systems: A network science approach," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-28, February.
    9. Brandtjen, Roland, 2023. "In varietate concordia - United in diversity: An analyze of the EU environment according to its motto," IU Discussion Papers - Business & Management 6 (Oktober 2023), IU International University of Applied Sciences.
    10. Xia, Yongxiang & Fan, Jin & Hill, David, 2010. "Cascading failure in Watts–Strogatz small-world networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(6), pages 1281-1285.
    11. Prentice, Catherine & Nguyen, Mai, 2021. "Robotic service quality – Scale development and validation," Journal of Retailing and Consumer Services, Elsevier, vol. 62(C).
    12. Leonardo Bargigli, 2013. "Statistical Equilibrium Models for Sparse Economic Networks," Working Papers - Economics wp2013_25.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    13. Jose Ribamar Siqueira Junior & Enrique Horst & German Molina & Laura H. Gunn & Felipe Reinoso-Carvalho & Burcu Sezen & Nathalie Peña-García, 2023. "Branding in the eye of the storm: the impact of brand ethical behavior on brand commitment during the COVID-19 crisis in a South American country," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(1), pages 95-115, March.
    14. Weihua Lei & Luiz G. A. Alves & Luís A. Nunes Amaral, 2022. "Forecasting the evolution of fast-changing transportation networks using machine learning," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    15. Di Gangi, Domenico & Lillo, Fabrizio & Pirino, Davide, 2018. "Assessing systemic risk due to fire sales spillover through maximum entropy network reconstruction," Journal of Economic Dynamics and Control, Elsevier, vol. 94(C), pages 117-141.
    16. Zhao, Jianyu & Wei, Jiang & Yu, Lean & Xi, Xi, 2022. "Robustness of knowledge networks under targeted attacks: Electric vehicle field of China evidence," Structural Change and Economic Dynamics, Elsevier, vol. 63(C), pages 367-382.
    17. Wasib Latif, 2022. "Determinants of Hotel Brand Image: A Unified Model of Customer-Based Brand Equity," International Journal of Customer Relationship Marketing and Management (IJCRMM), IGI Global, vol. 13(1), pages 1-20, January.
    18. Fabio Caccioli & Tiziana Di Matteo & Giulia Iori & Saqib Jafarey & Giacomo Livan & Simone Righi, 2022. "Introduction to the special issue on the 24th annual Workshop on Economic science with Heterogeneous Interacting Agents, London, 2019 (WEHIA 2019)," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 17(2), pages 401-404, April.
    19. Diego Kozlowski & Viktoriya Semeshenko & Andrea Molinari, 2021. "Latent Dirichlet allocation model for world trade analysis," PLOS ONE, Public Library of Science, vol. 16(2), pages 1-18, February.
    20. Paolo Bartesaghi & Gian Paolo Clemente & Rosanna Grassi, 2020. "Community structure in the World Trade Network based on communicability distances," Papers 2001.06356, arXiv.org, revised Jul 2020.

    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:spr:qualqt:v:52:y:2018:i:1:d:10.1007_s11135-016-0465-4. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.