Xiaoyan Fu, Seok-Hee Hong, Nikola S. Nikolov, Xiaobin Shen, Ying Xin Wu and Kai Xu, Visualization and Analysis of Email Networks, Proceedings of APVIS (Asia-Pacific Symposium on Visualisation) 2007, IEEE, pp.1-8, 2007.
This paper presents various methods for visualization and analysis
of email networks; visualization on the surface of a sphere to reveal
communication patterns between different groups, a hierarchical
drawing displaying the centrality analysis of nodes to emphasize
important nodes, a 2.5D visualization for temporal email networks
to analyze the evolution of email relationships changing over time,
and an ambient display for finding social circles derived from the
email network. Each method was evaluated with various data sets
from a research organization. We also extended our method for
visual analysis of an email virus network.
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Adel Ahmed, Tim Dwyer, Seok-Hee Hong, Colin Murray, Le Song, Ying Xin Wu, Visualisation and Analysis of Large and Complex Scale-free Networks, Proc. of EuroVis 2005 (EUROGRAPHICS-IEEE VGTC Symposium on Visualization), pp. 1-8, IEEE, 2005.
Scale-free networks appear in many application domains such as social and biological networks [BA99, BB03, BO04]. Roughly speaking, scale-free networks have power-law degree distribution, ultra-short average path length and high clustering coefficient. This paper presents new methods for visualising scale-free networks in three dimensions. To make effective use of the third dimension and minimise occlusion, we produce graph visulaisations with nodes constrained to lie on parallel planes or on the surface of spheres. We implement the algorithms using a variation of a fast force-directed graph layout method. Results with real world data sets such as IEEE InfoVis citation and collaboration networks and a protein-protein interaction network show that our method can be useful for visual analysis of large and complex scale-free networks. We also discuss the issue of visualisation of evolving networks and network integration
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A. Ahmed, X. Fu, S. Hong, Q. Nguyen and K. Xu, "Visual Analysis of History of World Cup: A Dynamic Network with Dynamic Hierarchy and Geographic Clustering", Visual Information Communication (Proceedings of VINCI'09), Springer, pp. 25-39, 2010.
In this paper, we present new visual analysis methods for history of
the FIFA World Cup competition data, a social network from Graph Drawing
2006 Competition. Our methods are based on the use of network analysis method,
and new visualization methods for dynamic graphs with dynamic hierarchy and
geographic clustering.
More specifically, we derive a dynamic network with geographic clustering from
the history of the FIFA World Cup competition data, based on who-beats-whom
relationship. Combined with the centrality analysis (which defines dynamic hierarchy)
and the use of the union of graphs (which determines the overall layout
topology), we present three new visualization methods for dynamic graphs with
dynamic hierarchy and geographic clustering: wheel layout, radial layout and hierarchical
layout.
Our experimental results show that our visual analysis methods can clearly reveal
the overall winner of the World Cup competition history as well as the strong
and weak countries. Further, one can analyze and compare the performance of
each country for each year along the context with their overall performance. This
enables to confirm the expected and discover the unexpected.
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Video
World Cup Movie1
World Cup Movie2
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