IDEAS home Printed from https://ideas.repec.org/p/ags/feemth/244529.html
   My bibliography  Save this paper

Exploring the Community Structure of Complex Networks

Author

Listed:
  • Drago, Carlo

Abstract

Regarding complex networks, one of the most relevant problems is to understand and to explore community structure. In particular it is important to define the network organization and the functions associated to the different network partitions. In this context, the idea is to consider some new approaches based on interval data in order to represent the different relevant network components as communities. The method is also useful to represent the network community structure, especially the network hierarchical structure. The application of the methodologies is based on the Italian interlocking directorship network.

Suggested Citation

  • Drago, Carlo, 2016. "Exploring the Community Structure of Complex Networks," ETA: Economic Theory and Applications 244529, Fondazione Eni Enrico Mattei (FEEM).
    • Handle: RePEc:ags:feemth:244529
    DOI: 10.22004/ag.econ.244529
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/244529/files/NDL2016-057.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.244529?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
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Zenou, Yves & Dequiedt, Vianney, 2014. "Local and Consistent Centrality Measures in Networks," Research Papers in Economics 2014:4, Stockholm University, Department of Economics.
    2. Piccardi, Carlo & Calatroni, Lisa & Bertoni, Fabio, 2010. "Communities in Italian corporate networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(22), pages 5247-5258.
    3. Carlo Drago & Roberto Ricciuti & Paolo Santella, 2015. "An Attempt to Disperse the Italian Interlocking Directorship Network: Analyzing the Effects of the 2011 Reform," Working Papers 11/2015, University of Verona, Department of Economics.
    4. Drago, Carlo & Millo, Francesco & Ricciuti, Roberto & Santella, Paolo, 2015. "Corporate governance reforms, interlocking directorship and company performance in Italy," International Review of Law and Economics, Elsevier, vol. 41(C), pages 38-49.
    5. Lucia Bellenzier & Rosanna Grassi, 2014. "Interlocking directorates in Italy: persistent links in network dynamics," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 9(2), pages 183-202, October.
    6. Billard L. & Diday E., 2003. "From the Statistics of Data to the Statistics of Knowledge: Symbolic Data Analysis," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 470-487, January.
    7. Paula Brito & A. Pedro Duarte Silva, 2012. "Modelling interval data with Normal and Skew-Normal distributions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(1), pages 3-20, March.
    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. Drago, Carlo, 2015. "Exploring the Community Structure of Complex Networks," MPRA Paper 81024, University Library of Munich, Germany.
    2. Drago, Carlo & Ricciuti, Roberto, 2017. "Communities detection as a tool to assess a reform of the Italian interlocking directorship network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 91-104.
    3. An Zeng & Stefano Battiston, 2016. "The Multiplex Network of EU Lobby Organizations," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-15, October.
    4. Carlo Drago & Roberto Ricciuti, 2019. "Bootstrapping the Gini Index of the Network Degree: An Application for Italian Corporate Governance," Working Papers 05/2019, University of Verona, Department of Economics.
    5. Andrea Fracasso & Valentina Peruzzi & Chiara Tomasi, 2024. "Multiple banking relationships: the role of firm connectedness," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 33(5), pages 1231-1252.
    6. A. Pedro Duarte Silva & Peter Filzmoser & Paula Brito, 2018. "Outlier detection in interval data," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 12(3), pages 785-822, September.
    7. Samadi, S. Yaser & Billard, Lynne, 2021. "Analysis of dependent data aggregated into intervals," Journal of Multivariate Analysis, Elsevier, vol. 186(C).
    8. Liang-Ching Lin & Hsiang-Lin Chien & Sangyeol Lee, 2021. "Symbolic interval-valued data analysis for time series based on auto-interval-regressive models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 295-315, March.
    9. Carlo Drago & Roberto Ricciuti & Paolo Santella, 2015. "An Attempt to Disperse the Italian Interlocking Directorship Network: Analyzing the Effects of the 2011 Reform," Working Papers 2015.82, Fondazione Eni Enrico Mattei.
    10. Sun, Yuying & Zhang, Xinyu & Wan, Alan T.K. & Wang, Shouyang, 2022. "Model averaging for interval-valued data," European Journal of Operational Research, Elsevier, vol. 301(2), pages 772-784.
    11. Bargigli, L. & Giannetti, R., 2018. "The Italian corporate system in a network perspective (1952–1983)," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 367-379.
    12. A. Silva & Paula Brito, 2015. "Discriminant Analysis of Interval Data: An Assessment of Parametric and Distance-Based Approaches," Journal of Classification, Springer;The Classification Society, vol. 32(3), pages 516-541, October.
    13. Battaggion, Maria Rosa & Cerasi, Vittoria, 2020. "Strategic interlocking directorates," Journal of Economic Behavior & Organization, Elsevier, vol. 178(C), pages 85-101.
    14. Su Kun & Liu Heng, 2019. "The Effect of Interlocking Director Network on Corporate Risk Taking: Lessons from China," Entrepreneurship Research Journal, De Gruyter, vol. 9(1), pages 1-21, January.
    15. Leonardo Bargigli & Renato Giannetti, 2015. "The Italian Corporate System: SOEs, Private Firms and Institutions in a Network Perspective (1952-1983)," Working Papers - Economics wp2015_01.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
    16. Eufr�sio de A. Lima Neto & Ulisses U. dos Anjos, 2015. "Regression model for interval-valued variables based on copulas," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(9), pages 2010-2029, September.
    17. M. Rosário Oliveira & Margarida Azeitona & António Pacheco & Rui Valadas, 2022. "Association measures for interval variables," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 16(3), pages 491-520, September.
    18. Sankowska, Anna & Siudak, Dariusz, 2016. "The small world phenomenon and assortative mixing in Polish corporate board and director networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 309-315.
    19. Karel Hron & Paula Brito & Peter Filzmoser, 2017. "Exploratory data analysis for interval compositional data," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 11(2), pages 223-241, June.
    20. Maria Rosa Battaggion & Vittoria Cerasi, 2018. "Endogenous interlocking directorates," Working Papers 380, University of Milano-Bicocca, Department of Economics, revised 01 May 2018.

    More about this item

    Keywords

    Research Methods/ Statistical Methods;

    JEL classification:

    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation

    Statistics

    Access and download statistics

    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:ags:feemth:244529. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/feemmit.html .

    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.