A Multi-Scale Similarity Network Approach to Mobility Profile Detection | 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-Scale Similarity Network Approach to Mobility Profile Detection Ogün Yilmaz, Hesham Ali, Andreas Pester This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9228955/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Population-level mobility is increasingly studied using wearable and urban audit data, yet most analyses rely on regression or centroid-based clustering that over-look structural similarity patterns. As populations age globally, understanding how activity variability is embedded within demographic and environmental configurations becomes critical for interpreting mobility inequalities. We propose a multi-scale similarity network framework that represents countries and cities as nodes in standardized multidimensional feature space and connects them via k-nearest-neighbor cosine similarity. At the country level, we integrate step inequality, gender gaps, urbanization, and HALE60 to examine structural profiles of mobility and healthy ageing context. At the city level, we apply the same framework to microscale walkability indicators to evaluate whether profile structure generalizes across analytical scales. Community detection and centrality analysis reveal stable similarity profiles and bridge entities not recoverable through partition-based clustering alone. Robustness evaluation using Adjusted Rand Index confirms profile stability under parameter perturbation. The results demonstrate that similarity-based network modeling provides a scale-agnostic structural lens for comparative mobil-ity research and supports policy interpretation in the context of age-supportive environments. Similarity networks kNN graphs cosine similarity community detection betweenness centrality activity inequality walkability healthy ageing Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 30 Apr, 2026 Reviewers agreed at journal 28 Apr, 2026 Reviewers invited by journal 28 Apr, 2026 Editor assigned by journal 26 Mar, 2026 Submission checks completed at journal 26 Mar, 2026 First submitted to journal 25 Mar, 2026 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. 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