Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/115434
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dc.contributorDepartment of Land Surveying and Geo-Informaticsen_US
dc.creatorLiao, Men_US
dc.creatorLiu, Xen_US
dc.date.accessioned2025-09-25T07:01:03Z-
dc.date.available2025-09-25T07:01:03Z-
dc.identifier.issn1009-5020en_US
dc.identifier.urihttp://hdl.handle.net/10397/115434-
dc.language.isoenen_US
dc.publisherTaylor & Francis Asia Pacific (Singapore)en_US
dc.rights© 2025 Wuhan University. Published by Informa UK Limited, trading as Taylor & Francis Group.en_US
dc.rightsThis is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.en_US
dc.rightsThe following publication Liao, M., & Liu, X. (2025). Exploring human mutuality in cyber and physical spaces using mobile big data and network analysis. Geo-Spatial Information Science, 1–17 is available at https://doi.org/10.1080/10095020.2025.2541072.en_US
dc.subjectCommunity detectionen_US
dc.subjectComplex networken_US
dc.subjectCyber spaceen_US
dc.subjectHuman mutualityen_US
dc.titleExploring human mutuality in cyber and physical spaces using mobile big data and network analysisen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.doi10.1080/10095020.2025.2541072en_US
dcterms.abstractPartially due to the limited access to datasets of human activities in cyber and physical (online and offline) spaces, the exploration of weak human interactions, defined as human mutuality in this work (i.e. co-location in physical space, and co-domain in cyber space) and their networks in the two spaces have been constrained to some extent in recent years. To bridge this gap, this study establishes a unified framework for directly comparing individual-level human mutuality networks across physical and cyber spaces, based on large-scale Uniform Resource Locators (URLs) data from tens of thousands of users in Jilin, China. Within this framework, human mutuality networks are constructed with users as nodes and mutuality events as edges, based on shared locations or shared website visits. The networks are systematically analyzed through three dimensions: fundamental network properties (such as clustering coefficient and average shortest path length), degree and strength distributions, and community structures. The results show distinct structural differences between the two spaces. Cyber space displays a significantly shorter average shortest path length (2.4) than the physical space (7.6), suggesting faster information transmission and the potential to alleviate digital inequalities by accelerating access to resources. Both networks present heavy-tailed degree distributions, indicating heterogeneous structures shaped by a few highly connected individuals. Furthermore, while physical space exhibits numerous small communities with strong local clustering, cyber space contains fewer but larger communities, with weaker local cohesion. This reduced local clustering may increase the risk of rapid misinformation diffusion. Additionally, the formation of cyber communities based on shared online behaviors reveals potential socioeconomic similarities among users despite differences in their physical attributes. Together, these insights offer a foundation for understanding human interactions across hybrid spaces and inform strategies for managing cyber and physical social dynamics.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationGeo-spatial information science (地球空间信息科学学报), Published online: 14 Aug 2025, Latest Articles, https://doi.org/10.1080/10095020.2025.2541072en_US
dcterms.isPartOfGeo-spatial information science (地球空间信息科学学报)en_US
dcterms.issued2025-
dc.identifier.scopus2-s2.0-105013280244-
dc.identifier.eissn1993-5153en_US
dc.description.validate202509 bcelen_US
dc.description.oaVersion of Recorden_US
dc.identifier.SubFormIDG000155/2025-09-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThis work is supported by the Research Institute for Land and Space (RILS) [Grant number 1-CD7M] at the Hong Kong Polytechnic University and the National Natural Science Foundation of China (NSFC) [Grant number 42171455].en_US
dc.description.pubStatusEarly releaseen_US
dc.description.oaCategoryCCen_US
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