The changing usage of a mature campus-wide wireless network
Proceedings of the 10th annual international conference on Mobile computing and networking
Reality mining: sensing complex social systems
Personal and Ubiquitous Computing
Visualizing community detection in opportunistic networks
Proceedings of the second ACM workshop on Challenged networks
Bubble rap: social-based forwarding in delay tolerant networks
Proceedings of the 9th ACM international symposium on Mobile ad hoc networking and computing
Distinct types of hubs in human dynamic networks
Proceedings of the 1st Workshop on Social Network Systems
Proceedings of the second ACM SIGCOMM workshop on Networking, systems, and applications on mobile handhelds
Getting real: a naturalistic methodology for using smartphones to collect mediated communications
Advances in Human-Computer Interaction
Centrality and mode detection in dynamic contact graphs; a joint diagonalisation approach
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
A Comparison of Opportunistic Connection Datasets
International Journal of Distributed Systems and Technologies
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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.