ACM Home Page
Please provide us with feedback. Feedback
DL HomeProceedingsMobiComCHANTS '08Citation
Visualizing communities and centralities from encounter traces
Full text PdfPdf (421 KB)
International Conference on Mobile Computing and Networking archive
Proceedings of the third ACM workshop on Challenged networks table of contents
San Francisco, California, USA
POSTER SESSION: Demo and poster session table of contents
Pages 129-132  
Year of Publication: 2008
Eiko Yoneki  University of Cambridge, Cambridge, United Kngdm
SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
ACM: Association for Computing Machinery
ACM  New York, NY, USA
Downloads (6 Weeks): 28,   Downloads (12 Months): 28,   Citation Count: 0
Additional Information:

abstract   references   index terms   collaborative colleagues  

Tools and Actions: Review this Article  
Save this Article to a Binder    Display Formats: BibTex  EndNote ACM Ref   
DOI Bookmark: Use this link to bookmark this Article:
What is a DOI?


We have previously demonstrated that information about social relationships can yield improved performance when it is used to control epidemic forwarding. We believe that extensive work to model human connectivity -- incorporating notions of community and interaction 'weight' -- is required if we are to understand this phenomenon and build networks that capitalize on it. This paper describes a visualization of detected community structures uncovered by different methods from human encounter traces. We focus on extracting information related to levels of clustering, network transitivity, and strong community structure. The position change of hub nodes within the network is also visualized.


Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

D. College., 2007.
L. Danon, J. Duch, A. Diaz-Guilera, and A. Arenas. Comparing community structure identification, 2005.
Haggle Project,, 2008.
N. Eagle et al. Reality mining: sensing complex social systems. Personal and Ubiquitous Computing, 10(4):255--268, 2006.
M. Fiedler. A property of eigenvectors of nonnegative symmetric matrices and its application to graph theory. Czech Math J., 25, 1975.
T. Henderson et al. The changing usage of a mature campus-wide wireless network. In Proc. Mobicom, 2004.
P. Hui et al. BUBBLE Rap: Social Based Forwarding in Delay Tolerant Networks. In proc. MobiHoc, 2008.
M. Newman. Analysis of weighted networks. Physical Review E, 70:056131, 2004.
M. Newman. Detecting community structure in networks. Eur. Phys. J. B, 38:321--330, 2004.
E. Yoneki et al. Visualizing Community Detection in Opportunistic Networks. In ACM CHANTS, 2007.
E. Yoneki et al. Distinct Types of Hubs in Human Dynamic Network. In EuroSys Socnet, 2008.