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SUMMARY:Temporal analysis and small world properties  of social and techno
 logical networks. - Cecillia Mascolo\, University of Cambridge\, Computer 
 Laboratory.
DTSTART:20091116T143000Z
DTEND:20091116T153000Z
UID:TALK20894@talks.cam.ac.uk
CONTACT:Neil Walton
DESCRIPTION:The analysis of social and technological networks has attracte
 d a lot of attention as social networking applications\nand mobile sensing
  devices have given us a wealth of real data. Classic studies looked at an
 alysing static or aggregated networks\, i.e.\, networks that do not change
  over time or built as the results of aggregation of information over a ce
 rtain period of time. Given the soaring collections of measurements relate
 d to very large\, real network traces\, researchers are quickly starting t
 o realise that connections are inherently varying over time and exhibit mo
 re dimensionality than static analysis can capture.\n\nIn this talk we pro
 pose new temporal distance metrics to quantify and compare the speed (dela
 y) of information dffusion processes taking into account the evolution of 
 a network from a local and global view. We show how these metrics are able
  to capture the temporal characteristics of time-varying graphs\, such as 
 delay\, duration and time order of contacts (interactions)\, compared to t
 he metrics used in the past on static graphs. We will also describe our st
 udy of small world properties of time varying networks.\n\nAs a proof of c
 oncept we apply these techniques to various time-varying networks\, namely
  connectivity of mobile devices\, facebook traces and brain cortical netwo
 rks.\n\nMore information about the work can be found at: http://www.cl.cam
 .ac.uk/research/srg/netos/spatialtemporalnetworks/\n
LOCATION:MR12\, CMS\, Wilberforce Road\, Cambridge\, CB3 0WB
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