From fuzzy information to community detection: an approach to social networks analysis with soft information

dc.contributor.authorGutiérrez García-Pardo, Inmaculada
dc.contributor.authorGómez González, Daniel
dc.contributor.authorCastro Cantalejo, Javier
dc.contributor.authorEspínola Vílchez, María Rosario
dc.contributor.editorWierzchoń, Sławomir T.
dc.date.accessioned2024-02-07T17:29:08Z
dc.date.available2024-02-07T17:29:08Z
dc.date.issued2022-11-19
dc.description.abstractOn 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.
dc.description.departmentDepto. de Estadística y Ciencia de los Datos
dc.description.facultyFac. de Estudios Estadísticos
dc.description.refereedTRUE
dc.description.statuspub
dc.identifier.citationGutiérrez, I.; Gómez, D.; Castro, J.; Espínola, R. From Fuzzy Information to Community Detection: An Approach to Social Networks Analysis with Soft Information. Mathematics 2022, 10, 4348. https://doi.org/10.3390/ math10224348
dc.identifier.doi10.3390/math10224348
dc.identifier.essn2227-7390
dc.identifier.officialurlhttps://www.mdpi.com/2227-7390/10/22/4348
dc.identifier.urihttps://hdl.handle.net/20.500.14352/100106
dc.issue.number22
dc.journal.titleMathematics
dc.language.isoeng
dc.page.final22
dc.page.initial1
dc.publisherMDPI
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-116884GB-I00/ES/MODELOS DE ATRIBUCION JUEGO-TEORICOS Y APLICACIONES: REDES SOCIALES, MARKETING Y MACHINE LEARNING/
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PGC2018-096509-B-I00/ES/GESTION INTELIGENTE DE INFORMACION BORROSA/
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationalen
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject.cdu519.22-7
dc.subject.cdu004.6
dc.subject.cdu519.226
dc.subject.keywordSoft information
dc.subject.keywordFuzzy sets
dc.subject.keywordLinguistic terms
dc.subject.keywordExtended fuzzy graph
dc.subject.keywordSocial network analysis
dc.subject.keywordCommunity detection problem
dc.subject.ucmEstadística aplicada
dc.subject.ucmTeoría de la decisión
dc.subject.unesco1208.07 Plausibilidad
dc.subject.unesco1209.03 Análisis de Datos
dc.titleFrom fuzzy information to community detection: an approach to social networks analysis with soft information
dc.typejournal article
dc.type.hasVersionVoR
dc.volume.number10
dspace.entity.typePublication
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