Understanding Social Characteristic from Spatial Proximity in Mobile Social Network

Duan Hu, Benxiong Huang, Lai Tu, Shu Chen


Over the past decades, cities as gathering places of millions of people rapidly evolved in all aspects of population, society, and environments. As one recent trend, location-based social networking applications on mobile devices are becoming increasingly popular. Such mobile devices also become data repositories of massive human activities. Compared with sensing applications in traditional sensor network, Social sensing application in mobile social network, as in which all individuals are regarded as numerous sensors, would result in the fusion of mobile, social and sensor data. In particular, it has been observed that the fusion of these data can be a very powerful tool for series mining purposes. A clear knowledge about the interaction between individual mobility and social networks is essential for improving the existing individual activity model in this paper. We first propose a new measurement called geographic community for clustering spatial proximity in mobile social networks. A novel approach for detecting these geographic communities in mobile social networks has been proposed. Through developing a spatial proximity matrix, an improved symmetric nonnegative matrix factorization method (SNMF) is used to detect geographic communities in mobile social networks. By a real dataset containing thousands of mobile phone users in a provincial capital of China, the correlation between geographic community and common social properties of users have been tested. 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. Several experimental results have been shown to verify the feasibility of this proposed hybrid approach based on the MIT dataset.


Mobile social network; Geographic community; Community structure; Measurement

Full Text:



D. Brockmann, L. Hufnagel, and T. Geisel (2006); The scaling laws of human travel, Nature, 439:462-465.

L. Hufnagel, D. Brockmann, and T. Geisel (2004); Forecast and control of epidemics in a globalized world, Proceedings of the National Academy of Sciences of the United States of America, 101(42):15124-15129.

C. Song, Z. Qu, N. Blumm, A. Barabasi (2010); Limits of predictability in human mobility, Science, 327(5968): 1018-1021.

E. Cho, S. A. Myers, and S. J. Leskovec(2011); Friendship and mobility: User movement in location-based social networks, Proc. of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining, New York, USA, 1082-1090.

D. Wang, D. Pedreschi, C. Song, F. Giannotti, and A. Barabasi (2011); Human mobility, social ties, and link prediction, Proc. of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining, New York, USA, 1100-1108.

N. Eagle, A. Pentland, and D. Lazer (2009);Inferring friendship network structure by using mobile phone data, Proc. of the National Academy of Sciences, 106(36): 15274-15278.

L. Backstrom, E. Sun, and C. Marlow (2010); Find me if you can: improving geographical prediction with social and spatial proximity, Proc. of the 19th international conference on World wide web(WWW'10), New York, USA, 61-70.

M. C. Gonzalez, C. A.Hidalgo, and A. Barabasi (2008); Understanding individual human mobility patterns, Nature, 453: 779-782.

Understanding individual human mobility patterns, Nature, 453: 779-782.

R. N. Mantegna and H. E. Stanley (1994); Stochastic process with ultraslow convergence to a Gaussian: the truncated Levy flight, Physical Review Letters, 73: 2946-2949.

C. Song, T. Koren, and A. Barabasi (2010); Modelling the scaling properties of human mobility, Nature Physics, 6: 818-823.

M. T. Rivera, S. B. Soderstrom, and B. Uzzi (2010); Dynamics of dyads in social networks: Assortative, relational, and proximity mechanisms, Annual Review of Sociology, 36: 91-115.

Q. Hao, et al. (2010); Equip tourists with knowledge mined from travelogues, Proceedings of the 19th international conference on World wide web (WWW'10), New York, USA, 401-410.

F. Wang, et al. (2011); Community discovery using nonnegative matrix factorization, Data Mining and Knowledge Discovery, 22: 493-521.

Q. Li, et al. (2008); Mining user similarity based on location history, Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems(GIS'08), Irvine, CA, USA, 34-43.

D. Wang, T. Li, S. Zhu, and C. Ding (2008); Multi-document summarization via sentencelevel semantic analysis and symmetric matrix factorization, Proc. of the 31st annual international ACM SIGIR conference on Research and development in information retrieval( SIGIR'08 ), New York, NY, 307-314.

S. Fortunato (2010); Community detection in graphs, Physics Reports, 486: 75-174.

L. Lu and T. Zhou (2011); Link prediction in complex networks: A survey, Physica A: Statistical Mechanics and its Applications, 390: 1150-1170.

N. P. Nguyen, et al. (2011); Adaptive algorithms for detecting community structure in dynamic social networks, Proc.IEEE INFOCOM, Shanghai,China, 2282-2290.

DOI: https://doi.org/10.15837/ijccc.2015.4.1991

Copyright (c) 2017 Duan Hu, Benxiong Huang, Lai Tu, Shu Chen

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

CC-BY-NC  License for Website User

Articles published in IJCCC user license are protected by copyright.

Users can access, download, copy, translate the IJCCC articles for non-commercial purposes provided that users, but cannot redistribute, display or adapt:

  • Cite the article using an appropriate bibliographic citation: author(s), article title, journal, volume, issue, page numbers, year of publication, DOI, and the link to the definitive published version on IJCCC website;
  • Maintain the integrity of the IJCCC article;
  • Retain the copyright notices and links to these terms and conditions so it is clear to other users what can and what cannot be done with the  article;
  • Ensure that, for any content in the IJCCC article that is identified as belonging to a third party, any re-use complies with the copyright policies of that third party;
  • Any translations must prominently display the statement: "This is an unofficial translation of an article that appeared in IJCCC. Agora University  has not endorsed this translation."

This is a non commercial license where the use of published articles for commercial purposes is forbiden. 

Commercial purposes include: 

  • Copying or downloading IJCCC articles, or linking to such postings, for further redistribution, sale or licensing, for a fee;
  • Copying, downloading or posting by a site or service that incorporates advertising with such content;
  • The inclusion or incorporation of article content in other works or services (other than normal quotations with an appropriate citation) that is then available for sale or licensing, for a fee;
  • Use of IJCCC articles or article content (other than normal quotations with appropriate citation) by for-profit organizations for promotional purposes, whether for a fee or otherwise;
  • Use for the purposes of monetary reward by means of sale, resale, license, loan, transfer or other form of commercial exploitation;

    The licensor cannot revoke these freedoms as long as you follow the license terms.

[End of CC-BY-NC  License for Website User]

INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL (IJCCC), With Emphasis on the Integration of Three Technologies (C & C & C),  ISSN 1841-9836.

IJCCC was founded in 2006,  at Agora University, by  Ioan DZITAC (Editor-in-Chief),  Florin Gheorghe FILIP (Editor-in-Chief), and  Misu-Jan MANOLESCU (Managing Editor).

Ethics: This journal is a member of, and subscribes to the principles of, the Committee on Publication Ethics (COPE).

Ioan  DZITAC (Editor-in-Chief) at COPE European Seminar, Bruxelles, 2015:

IJCCC is covered/indexed/abstracted in Science Citation Index Expanded (since vol.1(S),  2006); JCR2018: IF=1.585..

IJCCC is indexed in Scopus from 2008 (CiteScore2018 = 1.56):

Nomination by Elsevier for Journal Excellence Award Romania 2015 (SNIP2014 = 1.029): Elsevier/ Scopus

IJCCC was nominated by Elsevier for Journal Excellence Award - "Scopus Awards Romania 2015" (SNIP2014 = 1.029).

IJCCC is in Top 3 of 157 Romanian journals indexed by Scopus (in all fields) and No.1 in Computer Science field by Elsevier/ Scopus.


 Impact Factor in JCR2018 (Clarivate Analytics/SCI Expanded/ISI Web of Science): IF=1.585 (Q3). Scopus: CiteScore2018=1.56 (Q2);

SCImago Journal & Country Rank

Editors-in-Chief: Ioan DZITAC & Florin Gheorghe FILIP.