IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i22p4348-d977776.html
   My bibliography  Save this article

From Fuzzy Information to Community Detection: An Approach to Social Networks Analysis with Soft Information

Author

Listed:
  • Inmaculada Gutiérrez

    (Facultad de Estudios Estadísticos, Universidad Complutense de Madrid, 28040 Madrid, Spain)

  • Daniel Gómez

    (Facultad de Estudios Estadísticos, Universidad Complutense de Madrid, 28040 Madrid, Spain
    Instituto de Evaluación Sanitaria, Universidad Complutense de Madrid, 28040 Madrid, Spain)

  • Javier Castro

    (Facultad de Estudios Estadísticos, Universidad Complutense de Madrid, 28040 Madrid, Spain
    Instituto de Evaluación Sanitaria, Universidad Complutense de Madrid, 28040 Madrid, Spain)

  • Rosa Espínola

    (Facultad de Estudios Estadísticos, Universidad Complutense de Madrid, 28040 Madrid, Spain
    Instituto de Evaluación Sanitaria, Universidad Complutense de Madrid, 28040 Madrid, Spain)

Abstract

On the basis of network analysis, and within the context of modeling imprecision or vague information with fuzzy sets, we propose an innovative way to analyze, aggregate and apply this uncertain knowledge into community detection of real-life problems. This work is set on the existence of one (or multiple) soft information sources, independent of the network considered, assuming this extra knowledge is modeled by a vector of fuzzy sets (or a family of vectors). This information may represent, for example, how much some people agree with a specific law, or their position against several politicians. We emphasize the importance of being able to manage the vagueness which usually appears in real life because of the common use of linguistic terms. Then, we propose a constructive method to build fuzzy measures from fuzzy sets. These measures are the basis of a new representation model which combines the information of a network with that of fuzzy sets, specifically when it comes to linguistic terms. We propose a specific application of that model in terms of finding communities in a network with additional soft information. To do so, we propose an efficient algorithm and measure its performance by means of a benchmarking process, obtaining high-quality results.

Suggested Citation

  • Inmaculada Gutiérrez & Daniel Gómez & Javier Castro & Rosa Espínola, 2022. "From Fuzzy Information to Community Detection: An Approach to Social Networks Analysis with Soft Information," Mathematics, MDPI, vol. 10(22), pages 1-22, November.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:22:p:4348-:d:977776
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/22/4348/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/10/22/4348/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ludo Waltman & Nees Eck, 2013. "A smart local moving algorithm for large-scale modularity-based community detection," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 86(11), pages 1-14, November.
    2. Gomez, Daniel & Gonzalez-Aranguena, Enrique & Manuel, Conrado & Owen, Guillermo & del Pozo, Monica & Tejada, Juan, 2003. "Centrality and power in social networks: a game theoretic approach," Mathematical Social Sciences, Elsevier, vol. 46(1), pages 27-54, August.
    3. Daniel Gómez & Javier Castro & Inmaculada Gutiérrez & Rosa Espínola, 2021. "A New Edge Betweenness Measure Using a Game Theoretical Approach: An Application to Hierarchical Community Detection," Mathematics, MDPI, vol. 9(21), pages 1-29, October.
    4. Inmaculada Gutiérrez & Juan Antonio Guevara & Daniel Gómez & Javier Castro & Rosa Espínola, 2021. "Community Detection Problem Based on Polarization Measures: An Application to Twitter: The COVID-19 Case in Spain," Mathematics, MDPI, vol. 9(4), pages 1-27, February.
    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. Inmaculada Gutiérrez & Juan Antonio Guevara & Daniel Gómez & Javier Castro & Rosa Espínola, 2021. "Community Detection Problem Based on Polarization Measures: An Application to Twitter: The COVID-19 Case in Spain," Mathematics, MDPI, vol. 9(4), pages 1-27, February.
    2. Lutz Bornmann & Robin Haunschild & Sven E. Hug, 2018. "Visualizing the context of citations referencing papers published by Eugene Garfield: a new type of keyword co-occurrence analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(2), pages 427-437, February.
    3. Natalya Ivanova & Ekaterina Zolotova, 2023. "Landolt Indicator Values in Modern Research: A Review," Sustainability, MDPI, vol. 15(12), pages 1-22, June.
    4. Felix Fritz & Stefano Moretti & Jochen Staudacher, 2023. "Social Ranking Problems at the Interplay between Social Choice Theory and Coalitional Games," Mathematics, MDPI, vol. 11(24), pages 1-22, December.
    5. Nina Sakinah Ahmad Rofaie & Seuk Wai Phoong & Muzalwana Abdul Talib & Ainin Sulaiman, 2023. "Light-emitting diode (LED) research: A bibliometric analysis during 2003–2018," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(1), pages 173-191, February.
    6. Giovanni Matteo & Pierfrancesco Nardi & Stefano Grego & Caterina Guidi, 2018. "Bibliometric analysis of Climate Change Vulnerability Assessment research," Environment Systems and Decisions, Springer, vol. 38(4), pages 508-516, December.
    7. Yi-Ming Wei & Jin-Wei Wang & Tianqi Chen & Bi-Ying Yu & Hua Liao, 2018. "Frontiers of Low-Carbon Technologies: Results from Bibliographic Coupling with Sliding Window," CEEP-BIT Working Papers 116, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    8. Loredana Canfora & Corrado Costa & Federico Pallottino & Stefano Mocali, 2021. "Trends in Soil Microbial Inoculants Research: A Science Mapping Approach to Unravel Strengths and Weaknesses of Their Application," Agriculture, MDPI, vol. 11(2), pages 1-21, February.
    9. Sridhar Mandyam & Usha Sridhar, 2017. "DON and Shapley Value for Allocation among Cooperating Agents in a Network: Conditions for Equivalence," Studies in Microeconomics, , vol. 5(2), pages 143-161, December.
    10. Evi Sachini & Nikolaos Karampekios & Pierpaolo Brutti & Konstantinos Sioumalas-Christodoulou, 2020. "Should I stay or should I go? Using bibliometrics to identify the international mobility of highly educated Greek manpower," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 641-663, October.
    11. Natalya Ivanova & Ekaterina Zolotova, 2024. "Vegetation Dynamics Studies Based on Ellenberg and Landolt Indicator Values: A Review," Land, MDPI, vol. 13(10), pages 1-24, October.
    12. González–Arangüena, E. & Manuel, C. & Owen, G. & del Pozo, M., 2017. "The within groups and the between groups Myerson values," European Journal of Operational Research, Elsevier, vol. 257(2), pages 586-600.
    13. C. Manuel & D. Martín, 2021. "A value for communication situations with players having different bargaining abilities," Annals of Operations Research, Springer, vol. 301(1), pages 161-182, June.
    14. Francis Bloch & Matthew O. Jackson & Pietro Tebaldi, 2023. "Centrality measures in networks," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 61(2), pages 413-453, August.
    15. Belik, Ivan & Jörnsten, Kurt, 2015. "Shapley-Based Stackelberg Leadership Formation in Networks," Discussion Papers 2015/16, Norwegian School of Economics, Department of Business and Management Science.
    16. Vanessa Ioannoni & Tommaso Vitale & Corrado Costa & Iris Elliott, 2020. "Depicting communities of Romani studies: on the who, when and where of Roma related scientific publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(3), pages 1473-1490, March.
    17. van den Brink, René & Rusinowska, Agnieszka, 2022. "The degree measure as utility function over positions in graphs and digraphs," European Journal of Operational Research, Elsevier, vol. 299(3), pages 1033-1044.
    18. Massimo Aria & Corrado Cuccurullo & Luca D’Aniello & Michelangelo Misuraca & Maria Spano, 2022. "Thematic Analysis as a New Culturomic Tool: The Social Media Coverage on COVID-19 Pandemic in Italy," Sustainability, MDPI, vol. 14(6), pages 1-22, March.
    19. Trudeau, Christian & Vidal-Puga, Juan, 2020. "Clique games: A family of games with coincidence between the nucleolus and the Shapley value," Mathematical Social Sciences, Elsevier, vol. 103(C), pages 8-14.
    20. Tzuhua D. Lin & Nimrod D. Rubinstein & Nicole L. Fong & Megan Smith & Wendy Craft & Baby Martin-McNulty & Rebecca Perry & Martha A. Delaney & Margaret A. Roy & Rochelle Buffenstein, 2024. "Evolution of T cells in the cancer-resistant naked mole-rat," Nature Communications, Nature, vol. 15(1), pages 1-20, December.

    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:gam:jmathe:v:10:y:2022:i:22:p:4348-:d:977776. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.