UPDATED 6/9/2009

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Peking UniversityVisualMen

VAST 2009 Challenge
Challenge 2 - Social Network and Geospatial

Authors and Affiliations:

Xiaoru.yuan@gmail.com  [PRIMARY contact]

Jie Liu, Peking University

Hanqi Guo, Peking University

Peihong Guo, Peking University

Ning Zhang, Peking University

He Xiao, Peking University

Xin Zhang, Peking University

Heng Chen, Peking University

Xiaoru Yuan, Peking University [Faculty advisor]

 

Tool(s):

We used a graphs visualization tool which is developed by ourselves recently. This tool generates node-link graphs based on an improved spring model, providing features such as suspicious path detection and filtering. Interactions with the nodes are also permitted. Moreover, graphs combined with geo-information are also available in our tool, which enable us to analyze patterns related to geo-information.With the filtering feature analysts can choose some interested nodes for reviewing, which can greatly reduce cluttering in the graphs and can provide an overview of the graphs at different levels.

Analysts are free to choose their criteria for suspicious nodes and paths, and detected suspicious nodes and paths will be highlighted while others are hidden. The analyst can work with either the whole graphs or suspicious scenario. Our practice proofed this feature to be most valuable, for that combined with the filtering feature we are able to identify the criminal network in a few steps.

Nodes in the graphs can be moved manually, thus, analysts are free to make custom layout of the graphs. Graphs layout generated according to geo-information is also available. This graphs layout is overlaid on the given map, providing a clear overview of spatial relationships between the nodes.

 

 

Video:

 

video

 

ANSWERS:


MC2.1: Which of the two social structures, A or B, most closely match the scenario you have identified in the data?

A


MC2.2:  Provide the social network structure you have identified as a tab delimitated file. It should contain the employee, one or more handler, any middle folks, and the localized leader with their international contacts. What are the Flitter names of the persons involved? Please identify only key connections (not all single links for example) as well as any other nodes related to the scenario (if any) you may have discovered that were not described in the two scenarios A and B above.  Please name the file Flitter.txt and place it in the same directory as your index.htm file.  Please see the format required in the Task Descriptions.

Flitter.txt


MC2.3:  Characterize the difference between your social network and the closest social structure you selected (A or B). If you include extra nodes please explain how they fit in to your scenario or analysis. 

MC 2.3.doc


MC2.4:  How is your hypothesis about the social structure in Part 1 supported by the city locations of Flovania? What part(s), if any, did the role of geographical information play in the social network of part one? 

MC 2.4.doc


MC2.5:  In general, how are the Flitter users dispersed throughout the cities of this challenge? Which of the surrounding countries may have ties to this criminal operation?  Why might some be of more significant concern than others?

MC 2.5.doc