A Multi-objective Quantum Rotation-based Algorithm Enhanced for Overlapping Communities Detection in Social Networks

A Multi-objective Quantum Rotation-based Algorithm Enhanced for Overlapping Communities Detection in Social 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 A Multi-objective Quantum Rotation-based Algorithm Enhanced for Overlapping Communities Detection in Social Networks Ahmad Heydariyan, Farhad Soleimanian Gharehchopogh, Mohammadreza Ebrahimi Dishabi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6250690/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 3 You are reading this latest preprint version Abstract One of the critical operations in the analysis of social networks is community detection. Society is also a set of coherent vertices, where the internal communication of the society is more than the communication outside the society and in many real-world networks, communities can overlap. This paper employs an overlapping community detection using a multi-objective optimization approach based on learning automata that have been used to hybridize and avoid computational load intelligently. Artificial Gorilla Troops Optimizer (GTO), Fruit Fly Optimization (FFO) algorithms, and Quantum Rotary Gate (QRG) are used for this purpose and then integrated with the Pareto dominance technique. Also, fuzzy clustering and initialization strategies have been used for overlapping community detection. The tests conducted in this paper are based on 16 real-world data sets and synthetic data sets. The proposed model's findings were compared to existing optimization techniques, demonstrating that it outperforms the examined approaches. Quantum Rotating Gate Artificial Gorilla Troops Optimizer Fruit Fly Optimization Algorithms Fuzzy Clustering Overlapping Communities Detection Full Text Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 02 Apr, 2025 Reviewers invited by journal 02 Apr, 2025 First submitted to journal 20 Mar, 2025 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-6250690","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":437615913,"identity":"b07ab771-8be5-47c2-8929-2f1bd8a20d61","order_by":0,"name":"Ahmad Heydariyan","email":"","orcid":"","institution":"Department of Computer Engineering, Mi. 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