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Uncovering the spatial structure of mobility networks

Thomas Louail, Maxime Lenormand, Miguel Picornell, Oliva García Cantú, Ricardo Herranz, Enrique Frias-Martinez, José J. Ramasco, Marc Barthelemy
2015 Nature Communications  
Finally the method allows to determine categories of networks, and in the mobility case to classify cities according to their commuting structure.  ...  The extraction of a clear and simple footprint of the structure of large, weighted and directed networks is a general problem that has many applications.  ...  Supplementary Fig. 12 shows the values of J I versus the proportion f of reshuffled individuals, for different number of groups k.  ... 
doi:10.1038/ncomms7007 pmid:25607690 fatcat:uerqfvdklnfbja6dj3ubue5hci

Uncovering space-independent communities in spatial networks

P. Expert, T. S. Evans, V. D. Blondel, R. Lambiotte
2011 Proceedings of the National Academy of Sciences of the United States of America  
Extracting patterns and regularities from the resulting massive amount of human mobility data requires the development of appropriate tools for uncovering information in spatially-embedded networks.  ...  Methods are tested on a large mobile phone network and computer-generated benchmarks where the effect of space has been incorporated.  ...  R.L. acknowledges support from the UK EPSRC. This work was conducted within the framework of COST Action MP0801 Physics of Competition and Conflicts.  ... 
doi:10.1073/pnas.1018962108 pmid:21518910 pmcid:PMC3093492 fatcat:c6lkbl5b5jeybhtp2ijgpgyhmi

Familiar Strangers: the Collective Regularity in Human Behaviors [article]

Yan Leng, Dominiquo Santistevan, Alex Pentland
2018 arXiv   pre-print
With the help of the large-scale mobile phone records, we empirically show the existence of the relationship in the country of Andorra.  ...  Built upon the temporal and spatial distributions, we investigate the mechanisms, especially collective temporal regularity and spatial structure that trigger this phenomenon.  ...  By analyzing the temporal and spatial characteristics of the encounters, we uncover the underlying mechanisms, especially collective temporal regularity and spatial structure that trigger the phenomenon  ... 
arXiv:1803.08955v2 fatcat:wnr4ememrvbjjgjx77uz63kpry

Uncovering the Digital Divide and the Physical Divide in Senegal Using Mobile Phone Data [chapter]

Song Gao, Bo Yan, Li Gong, Blake Regalia, Yiting Ju, Yingjie Hu
2017 Advances in Geocomputation  
Conclusions In this work, we were trying to uncover the digital divide (phone communication patterns) and physical divide (human mobility patterns) in Senegal based on the large-scale mobile phone data  ...  The chosen spatial unit (e.g., cell-based, region-based) or temporal scale (e,g., by hour, day, week, month) might affect the results of analyzing human mobility and urban dynamics in the mobile age (  ... 
doi:10.1007/978-3-319-22786-3_14 fatcat:mbbckcsxo5huvb6ip6clvrxzpy


B. Fang, W. Tu, M. Li, J. Cao, W. Gao, Y. Yue, Q. Li
2022 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
Massive mobile phone location data contains hidden information of complex spatial networks.  ...  The results suggest that the PRD is with a significant trend of spatial synergy; the backbone of mobility network demonstrates that Guangzhou and Shenzhen are the spatial cores; the East-West differences  ...  ACKNOWLEDGEMENTS The study is jointly supported by the National Key Research and Development Project of China (No. 2019YFB2103104), Natural Science Foundation Project of China (42071360, 42101463), and  ... 
doi:10.5194/isprs-archives-xliii-b4-2022-521-2022 fatcat:fppw6lufmza6dd6aqv7v7x2uge

Interactional regions in cities: making sense of flows across networked systems

Kira Kempinska, Paul Longley, John Shawe-Taylor
2017 International Journal of Geographical Information Science  
The current state-of-the-art for uncovering interactional regions, i.e. regions reflective of observable human mobility and interaction patterns, is to apply community detection to networks constructed  ...  Secondly, it presents refinements of the topic modelling and community detection approaches that can uncover interaction patterns driven by forces other than spatial proximity.  ...  Acknowledgements This work is part of the project -Crime, Policing and Citizenship (CPC): Space-Time Interactions of Dynamic Networks (, supported by the UK Engineering and Physical Sciences  ... 
doi:10.1080/13658816.2017.1418878 fatcat:mczvvit5aza4lpnhdkvzaipctu

Exploring human movements in Singapore

Chaogui Kang, Stanislav Sobolevsky, Yu Liu, Carlo Ratti
2013 Proceedings of the 2nd ACM SIGKDD International Workshop on Urban Computing - UrbComp '13  
From a spatial network perspective, taxicab trips largely reflect interactions between further-separating locations than mobile phone movements, resulting in emergence of larger spatial communities (delineated  ...  has substantially different characteristics compared to taxicab trips, which are one of the frequently used means of transportation; (2) investigate the ratio of taxicab trips and mobile phone movements  ...  , GE, all the members of the MIT SENSEable City Lab Consortium and the China Scholarship Council for supporting the research.  ... 
doi:10.1145/2505821.2505826 dblp:conf/kdd/KangSLR13 fatcat:b4vso2tglvh33e6r4bm2e432zi

Location-aware computing to mobile services recommendation: Theory and practice

Honghao Gao, Andrés Muñoz, Wenbing Zhao, Yuyu Yin
2020 Journal of Ambient Intelligence and Smart Environments  
Specifically, the five-order tensor model consists of users, items, multiple ratings, spatial and temporal data, which keeps the latent structure of the interrelations between multi-criteria and spatial  ...  network monitoring based on Mobile CrowdSensing.  ...  Specifically, the five-order tensor model consists of users, items, multiple ratings, spatial and temporal data, which keeps the latent structure of the interrelations between multi-criteria and spatial  ... 
doi:10.3233/ais-200588 fatcat:kq5kxix6u5b3fcyopk7edkfs3i

Understanding core districts of city using human activity data

Duan Hu, Jie Yang, Benxiong Huang
2017 Advances in Modelling and Analysis B  
We further analyzed the functional role of these core districts in city. It provides a feasible approach to uncover spatial structure of an urban system.  ...  For "polycentric" urban systems, the role of city centers and their human flows's spatial influence on the surrounding area remain a challenging problem with many applications ranging from transportation  ...  Acknowledgements The authors are grateful for the support from the National Science Foundation of China (5147 9159).  ... 
doi:10.18280/ama_b.600114 fatcat:syzloombtbgb3jujgm7jq2bslq

Urban Analytics: Multiplexed and Dynamic Community Networks [article]

Weisi Guo, Guillem Mosquera Donate, Stephen Law, Samuel Johnson, Maria Liakata, Alan Wilson
2018 arXiv   pre-print
The better understanding of the structural dynamics and multiplexed relationships can provide useful information to inform both urban planning policies and shape the design of socially coupled urban infrastructure  ...  In this paper, we review how increasingly available heterogeneous mobile big data sets can be leveraged to detect the community interaction structure using natural language processing and machine learning  ...  Most of the interactions can be classified on a spatial axis, where the friction of the interaction determines whether the community network structure will be a spatially embedded network (i.e., walking-distance  ... 
arXiv:1706.05535v4 fatcat:xlhu2522jjf5xpswfqii6m3jmm

Uncovering regional characteristics from mobile phone data: A network science approach

Guanghua Chi, Jean-Claude Thill, Daoqin Tong, Li Shi, Yu Liu
2014 Papers in Regional Science  
This research demonstrates that networks built from mobile phone data provide new understandings of spatial interactions and regional structures. JEL classification: C18, R11, R58  ...  We introduce network science methods to uncover inherent characteristics of functional regions.  ...  interaction', we use mobile phone data to uncover the spatial structure of a region on the basis of the two network concepts of betweenness centrality and community.  ... 
doi:10.1111/pirs.12149 fatcat:mh7gltrwone65nsdrpcn7wtxnu

Regional economic status inference from information flow and talent mobility [article]

Jun Wang, Jian Gao, Jin-Hu Liu, Dan Yang, Tao Zhou
2019 arXiv   pre-print
We find that while the structural features of both networks are relevant to economic status, the talent mobility network in a relatively smaller size exhibits a stronger predictive power for the gross  ...  In this letter, we estimate the regional economic status based on the structural features of the two networks.  ...  This work was partially supported by the National Natural Science Foundation of China (Grant Nos. 61433014, 61603074, 61673086, and 61703074).  ... 
arXiv:1902.05218v1 fatcat:g7es4latlzdwfhf53hmvc6n7iu

Revealing Dynamic Spatial Structures of Urban Mobility Networks and the Underlying Evolutionary Patterns

Chun Liu, Li Chen, Quan Yuan, Hangbin Wu, Wei Huang
2022 ISPRS International Journal of Geo-Information  
Modelling urban spatial structures in the context of mobility and revealing their underlying patterns in dynamic networks are key to understanding urban spatial structures and how urban systems work.  ...  Last, the capability of the proposed framework is examined by an empirical analysis based on taxi mobility networks.  ...  A case study of Shanghai, China is conducted to validate the methods and to uncover the dynamic spatial structure of the city.  ... 
doi:10.3390/ijgi11040237 fatcat:lcginxbnpnbzpex32fvgp2haeu

Discovering Spatial Interaction Communities from Mobile Phone Data

Song Gao, Yu Liu, Yaoli Wang, Xiujun Ma
2013 Transactions on GIS  
The findings of this empirical study are valuable for urban structure studies as well as for the detection of communities in spatial networks.  ...  This research attempts to explore and interpret patterns embedded in the network of phone-call interaction and the network of phone-users' movements, by considering the geographical context of mobile phone  ...  In Section 2, we introduce the mobile phone datasets of the study area and preprocessing procedures for extracting networks of spatial interaction flow, as well as dynamic spatial structures of phone-call  ... 
doi:10.1111/tgis.12042 fatcat:yxk2cyrf7jg6rngt35vingbuzy

Understanding Social Characteristic from Spatial Proximity in Mobile Social Network

Duan Hu, Benxiong Huang, Lai Tu, Shu Chen
2015 International Journal of Computers Communications & Control  
While exploring shared individual movement patterns, we propose a hybrid approach that utilizes spatial proximity and social proximity of individuals for mining network structure in mobile social networks  ...  We first propose a new measurement called geographic community for clustering spatial proximity in mobile social networks.  ...  Spatial proximity and social proximity of individuals can be used for mining network structure in mobile social network.  ... 
doi:10.15837/ijccc.2015.4.1991 fatcat:v7mgggesqval5azlmu7rrkcvte
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