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Mobile cellular big data: linking cyberspace and the physical world with social ecology

Mobile cellular big data: linking cyberspace and the physical world with social ecology
Mobile cellular big data: linking cyberspace and the physical world with social ecology
Understanding mobile big data, inherent within large-scale cellular towers in the urban environment, is extremely valuable for service providers, mobile users, and government managers of the modern metropolis. By extracting and modeling the mobile cellular data associated with over 9600 cellular towers deployed in a metropolitan city of China, this article aims to link cyberspace and the physical world with social ecology via such big data. We first extract a human mobility and cellular traffic consumption trace from the dataset, and then investigate human behavior in cyberspace and the physical world. Our analysis reveals that human mobility and the consumed mobile traffic have strong correlations, and both have distinct periodical patterns in the time domain. In addition, both human mobility and mobile traffic consumption are linked with social ecology, which in turn helps us to better understand human behavior. We believe that the proposed big data processing and modeling methodology, combined with the empirical analysis on mobile traffic, human mobility, and social ecology, paves the way toward a deep understanding of human behaviors in a large-scale metropolis.
0890-8044
6-12
Xu, Fengli
6fc87c70-ee94-406a-915e-92d32be6b30e
Li, Yong
0817e950-114f-47f3-aefe-74bf9ec0e2a3
Chen, Min
8ba2b581-ac04-4528-bbfe-7daf7f18bd75
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Xu, Fengli
6fc87c70-ee94-406a-915e-92d32be6b30e
Li, Yong
0817e950-114f-47f3-aefe-74bf9ec0e2a3
Chen, Min
8ba2b581-ac04-4528-bbfe-7daf7f18bd75
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80

Xu, Fengli, Li, Yong, Chen, Min and Chen, Sheng (2016) Mobile cellular big data: linking cyberspace and the physical world with social ecology. IEEE Network, 30 (3), 6-12. (doi:10.1109/MNET.2016.7474338).

Record type: Article

Abstract

Understanding mobile big data, inherent within large-scale cellular towers in the urban environment, is extremely valuable for service providers, mobile users, and government managers of the modern metropolis. By extracting and modeling the mobile cellular data associated with over 9600 cellular towers deployed in a metropolitan city of China, this article aims to link cyberspace and the physical world with social ecology via such big data. We first extract a human mobility and cellular traffic consumption trace from the dataset, and then investigate human behavior in cyberspace and the physical world. Our analysis reveals that human mobility and the consumed mobile traffic have strong correlations, and both have distinct periodical patterns in the time domain. In addition, both human mobility and mobile traffic consumption are linked with social ecology, which in turn helps us to better understand human behavior. We believe that the proposed big data processing and modeling methodology, combined with the empirical analysis on mobile traffic, human mobility, and social ecology, paves the way toward a deep understanding of human behaviors in a large-scale metropolis.

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Accepted/In Press date: 20 February 2016
Published date: 20 May 2016
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 395479
URI: http://eprints.soton.ac.uk/id/eprint/395479
ISSN: 0890-8044
PURE UUID: 2a97c6ef-2de7-46ff-8baf-573a11b2120b

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Date deposited: 31 May 2016 10:57
Last modified: 16 Dec 2019 19:54

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Contributors

Author: Fengli Xu
Author: Yong Li
Author: Min Chen
Author: Sheng Chen

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