Abstract
Up to now, data of actual communication services obtained from communication networks, such as the volume of traffic and the number of users, has mainly been used to forecast traffic demands and provision network facilities. It can be said that this use focuses on the “quantitative” side of the data. On the other hand, such data can also illuminate several characteristics of the structures of the human society. This chapter introduces a new “qualitative” use of communication network data. We try to extract social information from the data, and investigate the universal structure of social networks that underlie the most popular communication services. Our expectation is that each communication service provides a different window on the universal social network structure. The question is how to access those windows.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
M. Aida, K. Ishibashi, H. Miwa, C. Takano, and S. Kuribayashi, “Structure of human relations and user-dynamics revealed by traffic data,” IEICE Transactions on Information and Systems, vol. E87-D, no. 6, pp. 1454–1460, 2004
M. Aida, K. Ishibashi, C. Takano, H. Miwa, K. Muranaka, and A. Miura, “Cluster structures in topology of large-scale social networks revealed by traffic data,” IEEE GLOBECOM 2005, St. Louis, 2005
DoCoMo Net, How the i-mode service is used. http://www.nttdocomo.co.jp/
Masaki Aida, Jun Sasaki, “Structural analysis on social networks using the spread process of communication services,” IEICE Tech. Rep., IN2006-41, vol. 106, no. 151, pp. 37–42, 2006 (in Japanese)
R. Rousseau, “George Kingsley Zipf: life, idea, his law and informetrics,” Glottometrics, vol. 3 (To Honor G.K. Zipf), pp. 11–18, 2002
A.-L. Barabási and R. Albert, “Emergence of scaling in random networks,” Science, vol. 286, pp. 509–512, 1999
R. Albert and A.-L. Barabási, “Statistical mechanics of complex networks,” Rev. Mod. Phys., vol. 74, no. 47, 2002
Masaki Aida, “Structures of social networks and user-dynamics revealed by power laws, Inspired from phenomenology,” Journal of IEICE, vol. 91, no. 10, pp. 891–896, 2008 (in Japanese)
mixi, Inc. http://mixi.co.jp/
K. Yuda, N. Ono, and Y. Fujiwara, “Human network structure in a social networking service,” Transactions of the Information Processing Society of Japan, vol. 47, no. 3, pp. 865–874, 2006 (in Japanese)
au by KDDI, http://www.au.kddi.com/
T. Hirano, M. Uwajima, C. Takano, and M. Aida, “Spreading strategy of communication service based on a social network model,” IEICE Tech. Rep., IN2008-135, vol. 108, no. 458, pp. 19–24, 2009 (in Japanese)
Acknowledgements
A part of this research was made possible by funds provided by the International Communication Foundation (ICF) (now KDDI Foundation) in its Research Support Program for fiscal year 2005, and by the Grant-in-Aid for Scientific Research (S) No. 18100001 (2006–2010) from the Japan Society for the Promotion of Science.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer Science+Business Media, LLC
About this chapter
Cite this chapter
Aida, M., Koto, H. (2010). Structure and Dynamics of Social Networks Revealed by Data Analysis of Actual Communication Services. In: Furht, B. (eds) Handbook of Social Network Technologies and Applications. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-7142-5_2
Download citation
DOI: https://doi.org/10.1007/978-1-4419-7142-5_2
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4419-7141-8
Online ISBN: 978-1-4419-7142-5
eBook Packages: Computer ScienceComputer Science (R0)