661
Views
1
CrossRef citations to date
0
Altmetric
Research Article

Spatio-temporal evolution of population mobility differentiation patterns in a pandemic context: based on a network perspective

, , &
Article: 2240945 | Received 11 May 2023, Accepted 20 Jul 2023, Published online: 30 Jul 2023

References

  • Barrat A, Barthélemy M, Pastor-Satorras R, Vespignani A. 2004. The architecture of complex weighted networks. Proc Natl Acad Sci USA. 101(11):3747–3752. doi: 10.1073/pnas.0400087101.
  • Blondel V, Guillaume J-L, Lambiotte R, Lefebvre E. 2008. Fast unfolding of communities in large networks. J Stat Mech Theory Exp. 2008(10):P10008.
  • Bonaccorsi G, Pierri F, Cinelli M, Flori A, Galeazzi A, Porcelli F, Schmidt AL, Valensise CM, Scala A, Quattrociocchi W, et al. 2020. Economic and social consequences of human mobility restrictions under COVID-19. Proc Natl Acad Sci USA. 117(27):15530–15535. doi: 10.1073/pnas.2007658117.
  • Boschma R. 2015. Towards an evolutionary perspective on regional resilience. Reg Stud. 49(5):733–751. doi: 10.1080/00343404.2014.959481.
  • Davis MA, Fisher JDM, Whited TM. 2014. Macroeconomic implications of agglomeration. Econometrica. 82(2):731–764.
  • Derudder BEN, Taylor P. 2005. The cliquishness of world cities. Glob Netw. 5(1):71–91. doi: 10.1111/j.1471-0374.2005.00108.x.
  • Fang Y, Wang J, Fu S, Zhai T, Huang L. 2022. Changes in ecological networks and eco-environmental effects on urban ecosystem in China’s typical urban agglomerations. Environ Sci Pollut Res Int. 29(31):46991–47010. doi: 10.1007/s11356-022-19226-7.
  • Fortunato S. 2010. Community detection in graphs. Phys Rep. 486(3–5):75–174. doi: 10.1016/j.physrep.2009.11.002.
  • García-Palomares JC, Salas-Olmedo MH, Moya-Gómez B, Condeço-Melhorado A, Gutiérrez J. 2018. City dynamics through Twitter: relationships between land use and spatiotemporal demographics. Cities. 72:310–319. doi: 10.1016/j.cities.2017.09.007.
  • Glaeser E. 2012. Triumph of the city: how our greatest invention makes us richer, smarter, greener, healthier, and happier.
  • Han J, Gao M, Sun Y. 2019. Research on the measurement and path of urban agglomeration growth effect. Sustainability. 11(19):5179. doi: 10.3390/su11195179.
  • He X, Yuan X, Zhang D, Zhang R, Li M, Zhou C. 2021. Delineation of urban agglomeration boundary based on multisource big data fusion—a case study of Guangdong–Hong Kong–Macao Greater Bay Area (GBA). Rem Sens. 13(9):1801. doi: 10.3390/rs13091801.
  • Kraemer MUG, Sadilek A, Zhang Q, Marchal NA, Tuli G, Cohn EL, Hswen Y, Perkins TA, Smith DL, Reiner RC, et al. 2020. Mapping global variation in human mobility. Nat Hum Behav. 4(8):800–810. doi: 10.1038/s41562-020-0875-0.
  • Kumar K, Castells M. 1997. The information age: economy, society and culture. Volume I. The rise of the network society. Br J Sociol. 48(3):524. doi: 10.2307/591145.
  • Li J, Ye Q, Deng X, Liu Y, Liu Y. 2016. Spatial-temporal analysis on spring festival travel rush in China based on multisource big data. Sustainability. 8(11):1184. doi: 10.3390/su8111184.
  • Lin J, Yang S, Liu Y, Zhu Y, Cai A. 2023. The urban population agglomeration capacity and its impact on economic efficiency in the Yangtze River Delta Urban Agglomeration. Environ Dev Sustain. 1–30. doi: 10.1007/s10668-023-03242-9.
  • Liu L. 2020. Emerging study on the transmission of the Novel Coronavirus (COVID-19) from urban perspective: evidence from China. Cities. 103:102759. doi: 10.1016/j.cities.2020.102759.
  • Liu W, Guo J, Wu W, Cao Y. 2022. The evolution of regional spatial structure influenced by passenger rail service: a case study of the Yangtze River Delta. Growth Change. 53(2):651–679. doi: 10.1111/grow.12601.
  • Liu W, Hou Q, Xie Z, Mai X. 2020. Urban network and regions in China: an analysis of daily migration with complex networks model. Sustainability. 12(8):3208. doi: 10.3390/su12083208.
  • Liu S, Xiao Q. 2021. An empirical analysis on spatial correlation investigation of industrial carbon emissions using SNA-ICE model. Energy. 224:120183. doi: 10.1016/j.energy.2021.120183.
  • Losacker S. 2022. ‘License to green’: regional patent licensing networks and green technology diffusion in China. Technol Forecast Social Change. 175:121336. doi: 10.1016/j.techfore.2021.121336.
  • Malik HAM. 2022. Complex network formation and analysis of online social media systems. Comput Model Eng Sci. 130(3):1737–1750.
  • Neal Z. 2011. Differentiating centrality and power in the world city network. Urb Stud. 48(13):2733–2748. doi: 10.1177/0042098010388954.
  • Neal Z. 2013. Does world city network research need eigenvectors? Urb Stud. 50(8):1648–1659. doi: 10.1177/0042098013477702.
  • Newman MEJ. 2006. Modularity and community structure in networks. Proc Natl Acad Sci USA. 103(23):8577–8582. doi: 10.1073/pnas.0601602103.
  • Onnela J-P, Saramäki J, Kertész J, Kaski K. 2005. Intensity and coherence of motifs in weighted complex networks. Phys Rev E Stat Nonlin Soft Matter Phys. 71(6 Pt 2):065103. doi: 10.1103/PhysRevE.71.065103.
  • Opsahl T, Agneessens F, Skvoretz J. 2010. Node centrality in weighted networks: generalizing degree and shortest paths. Soc Netw. 32(3):245–251. doi: 10.1016/j.socnet.2010.03.006.
  • Pan F, Fang C. 2022. Mapping global financial networks: a spatial analysis of Chinese companies’ overseas listings. Trans Plan Urb Res. 1(1–2):32–49. doi: 10.1177/27541223221116124.
  • Pan J, Lai J. 2019. Spatial pattern of population mobility among cities in China: case study of the National Day plus mid-autumn festival based on Tencent migration data. Cities. 94:55–69. doi: 10.1016/j.cities.2019.05.022.
  • Qazi A, Simsekler MCE, Akram M. 2021. Efficacy of early warning systems in assessing country-level risk exposure to COVID-19. Geomatics Nat Hazards Risk. 12(1):2352–2366. doi: 10.1080/19475705.2021.1962984.
  • Ruan J, Chen Y, Yang Z. 2021. Assessment of temporal and spatial progress of urban resilience in Guangzhou under rainstorm scenarios. Int J Disaster Risk Reduct. 66:102578. doi: 10.1016/j.ijdrr.2021.102578.
  • Santamaria C, Sermi F, Spyratos S, Iacus SM, Annunziato A, Tarchi D, Vespe M. 2020. Measuring the impact of COVID-19 confinement measures on human mobility using mobile positioning data. A European regional analysis. Saf Sci. 132:104925. doi: 10.1016/j.ssci.2020.104925.
  • Serbanica C, Constantin DL. 2023. Misfortunes never come singly. A holistic approach to urban resilience and sustainability challenges. Cities. 134:104177. doi: 10.1016/j.cities.2022.104177.
  • Shen W, Liang H, Dong L, Ren J, Wang G. 2021. Synergistic CO2 reduction effects in Chinese urban agglomerations: perspectives from social network analysis. Sci Total Environ. 798:149352. doi: 10.1016/j.scitotenv.2021.149352.
  • Sigler T, Martinus K, Loginova J. 2021. Socio-spatial relations observed in the global city network of firms. PLOS One. 16(8):e0255461. doi: 10.1371/journal.pone.0255461.
  • Taylor P, Derudder B. 2015. World city network: a global urban analysis. London: Routledge.
  • Wang L, Xue X, Zhou X, Wang Z, Liu R. 2021. Analyzing the topology characteristic and effectiveness of the China city network. Environ Plan B Urb Anal City Sci. 48(9):2554–2573. doi: 10.1177/2399808320983011.
  • Wu K, Wu J, Li Y. 2022. Mining typhoon victim information based on multi-source data fusion using social media data in China: a case study of the 2019 Super Typhoon Lekima. Geomatics Nat Hazards Risk. 13(1):1087–1105. doi: 10.1080/19475705.2022.2064774.
  • Xu S, Wang X, Zhu R, Wang D. 2023. Spatio-temporal effects of regional resilience construction on carbon emissions: evidence from 30 Chinese provinces. Sci Total Environ. 887:164109. doi: 10.1016/j.scitotenv.2023.164109.
  • Yang X, Derudder B, Taylor PJ, Ni P, Shen W. 2017. Asymmetric global network connectivities in the world city network, 2013. Cities. 60:84–90. doi: 10.1016/j.cities.2016.08.009.
  • Yang H, Hu S, Zheng X, Wu Y, Lin X, Xie L, Shen Z. 2022. Population migration, confirmed COVID-19 cases, pandemic prevention, and control: evidence and experiences from China. Z Gesundh Wiss. 30(5):1257–1263. doi: 10.1007/s10389-020-01403-y.
  • Zhao R, Fang C, Liu J, Zhang L. 2022. The evaluation and obstacle analysis of urban resilience from the multidimensional perspective in Chinese cities. Sustainable Cities and Society. 86:104160. doi: 10.1016/j.scs.2022.104160.
  • Zhao Z, Wei Y, WS, Pang R. 2017. Measurement of directed alternative centricity and power of directed weighted urban network: a case of population flow network of China during “Chunyun” period. Geogr Res. 36(4):647–660.
  • Zhu R, Wang Y, Lin D, Jendryke M, Xie M, Guo J, Meng L. 2021. Exploring the rich-club characteristic in internal migration: evidence from Chinese Chunyun migration. Cities. 114:103198. doi: 10.1016/j.cities.2021.103198.