UCAD: commUnity disCovery method in Attribute-based multicoloreD networks

UCAD: commUnity disCovery method in Attribute-based multicoloreD networks | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article UCAD: commUnity disCovery method in Attribute-based multicoloreD networks Félicité Gamgne Domgue, Norbert Tsopze, René Ndoundam This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3986554/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Many hierarchical methods for community detection in multicolored networks are capable of finding clusters when there are interslice correlation between layers. However, in general, they aggregate all the links in different layer treating them as being equivalent. Therefore, such aggregation might ignore the information about the relevance of a dimension in which the node is involved. In this paper we fill this gap by proposing a hierarchical classification based-Louvain method for interslice-multicolored networks. In particular we define a new node centrality measure named \textit{Attractivity} to describe the inter-slice correlation that incorporates within and across-dimension topological features in order to identify the relevant dimension. Then, after merging dimensions through a frequential aggregation, we group nodes by their relational and attribute similarity, where attributes correspond to their relevant dimensions. We conduct an extensive experimentation using seven real-world multicolored networks, which also includes comparison with state-of-the-art methods. Results show the significance of our proposed method in discovering relevant communities over multiple dimensions and highlight its ability in producing optimal covers with higher values of the multidimensional version of the modularity function. Attributed networks Multidimensionnal networks Community detection Modularity Overlapping Social Network Analysis Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 08 May, 2024 Reviews received at journal 23 Apr, 2024 Reviewers agreed at journal 16 Mar, 2024 Reviews received at journal 16 Mar, 2024 Reviewers agreed at journal 16 Mar, 2024 Reviewers agreed at journal 16 Mar, 2024 Reviewers invited by journal 16 Mar, 2024 Editor assigned by journal 12 Mar, 2024 Submission checks completed at journal 26 Feb, 2024 First submitted to journal 24 Feb, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3986554","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":274891361,"identity":"259f4cb4-8cf2-40ff-9736-0d6b5cdad409","order_by":0,"name":"Félicité Gamgne Domgue","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAElEQVRIiWNgGAWjYBAC9gbmhgMIbgUQMzM34NXCc4ARWcsZkBZGwloQPMY2MElAC3tj44EfFQx2/dOOX3vwcV5tNH87UMuPim24tfAcbDjYc4YhecbtnHLDmduO5844zNjA2HPmNk4t9hKJDYeB7klmuJ2TJs277VgukNvAzNiGWwuP/EOgmn8MyfIgLX/nHMudT1CLBCPIWAY7g9vpx6QZG2pyNxDUwpMI9MsxiQTD2zlskj3HDuRuBGo5iM8vPOyHD3/4UWNjL3c7/ZnEj5q63HnnDx988KMCtxYoAAYCA48BkHEYzD1ASD0I2APTzgMgXUeM4lEwCkbBKBhhAACRnGEYL90m8wAAAABJRU5ErkJggg==","orcid":"","institution":"University of Yaounde I","correspondingAuthor":true,"prefix":"","firstName":"Félicité","middleName":"Gamgne","lastName":"Domgue","suffix":""},{"id":274891362,"identity":"6f516e96-71a5-4154-860f-86a438e7e6f3","order_by":1,"name":"Norbert Tsopze","email":"","orcid":"","institution":"University of Yaounde I","correspondingAuthor":false,"prefix":"","firstName":"Norbert","middleName":"","lastName":"Tsopze","suffix":""},{"id":274891363,"identity":"54870b11-eb0b-444a-9ef0-50b6b7043a93","order_by":2,"name":"René Ndoundam","email":"","orcid":"","institution":"University of Yaounde I","correspondingAuthor":false,"prefix":"","firstName":"René","middleName":"","lastName":"Ndoundam","suffix":""}],"badges":[],"createdAt":"2024-02-25 02:18:39","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3986554/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3986554/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":51728716,"identity":"55a7aba7-5b3a-4f00-9deb-c9efa61a196b","added_by":"auto","created_at":"2024-02-28 03:49:00","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":762223,"visible":true,"origin":"","legend":"","description":"","filename":"UCADpaper2024maj.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3986554/v1_covered_469db562-9371-4f87-919e-49123f7d77c4.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"UCAD: commUnity disCovery method in Attribute-based multicoloreD networks","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"knowledge-and-information-systems","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"kais","sideBox":"Learn more about [Knowledge and Information Systems](http://link.springer.com/journal/10115)","snPcode":"10115","submissionUrl":"https://submission.nature.com/new-submission/10115/3","title":"Knowledge and Information Systems","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Attributed networks, Multidimensionnal networks, Community detection, Modularity, Overlapping, Social Network Analysis","lastPublishedDoi":"10.21203/rs.3.rs-3986554/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3986554/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Many hierarchical methods for community detection in multicolored networks are capable of finding clusters when there are interslice correlation between layers. \nHowever, in general, they aggregate all the links in different layer treating them as being equivalent. 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