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Integration of migration and attention flow data to reveal association of virtual–real dual intercity network structure.
- Source :
-
Cities . Dec2023, Vol. 143, pN.PAG-N.PAG. 1p. - Publication Year :
- 2023
-
Abstract
- The study of intercity network structure from the perspective of flow space can effectively reveal the connection patterns, hierarchical laws, and spatial organization of cities. However, current studies mostly focus on a single real or virtual space, neglecting the comprehensive perspective. Furthermore, the research subject of network relationships is usually the complex original aligned network rather than the spatially cohesive network structure. In this study, spatial network structures are constructed and extracted based on the migration flow and attention flow, which represent people's objective behavior and subjective will, respectively. This study then reveals the association between virtual and real networks from three aspects: node location, node attributes, and local network structure characteristics. Results indicate that compared with the real network structure, the virtual network structure has a strong same-level node agglomeration and a significant node size difference. Spatial dislocations are observed in the high association of the various measures of China's real and virtual network structures. The degree of differences in network structures between virtual and real spaces varies spatially. This paper reveals the dynamics of urban development in different spaces, helping build a human-centered, high-quality space governance system for virtual and real spaces. • Spatial network structure considering the geographical proximity and interaction strength among cities is extracted. • Location, attribution, and structure-based association analysis method for non-aligned intercity networks is proposed. • The degree of differences in network structures between virtual and real spaces varies spatially. • The association pattern between real and virtual networks is spatially dislocated in different indicators. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 02642751
- Volume :
- 143
- Database :
- Academic Search Index
- Journal :
- Cities
- Publication Type :
- Academic Journal
- Accession number :
- 173415261
- Full Text :
- https://doi.org/10.1016/j.cities.2023.104614