Fundamentals of Visualizing Communication Networks

被引:1
作者
Pfeffer, Juergen [1 ]
机构
[1] Carnegie Mellon Univ, Sch Comp Sci, Pittsburgh, PA 15213 USA
关键词
communication networks; information visualization; human perception;
D O I
10.1109/CC.2013.6488833
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
The human brain is built to process complex visual impressions within milliseconds. In comparison with sequentially coded spoken language and written texts, we are capable of consuming graphical information at a high bandwidth in a parallel fashion, producing a picture worth more than a thousand words. Effective information visualization can be a powerful tool to capture people's attention and quickly communicate large amounts of data and complex information. This is particularly important in the context of communication data, which often describes entities (people, organizations) and their connections through communication. Visual analytics approaches can optimize the user-computer interaction to gain insights into communication networks and learn about their structures. Network visualization is a perfect instrument to better communicate the results of analysis. The precondition for effective information visualization and successful visual reasoning is the capability to draw "good" pictures. Even though communication networks are often large, including thousands or even millions of people, underlying visualization principles are identical to those used for visualizing smaller networks. In this article, you will learn about these principles, giving you the ability to assess the quality of network visualizations and to draw better network pictures by yourself.
引用
收藏
页码:82 / 90
页数:9
相关论文
共 16 条
[1]  
[Anonymous], PSYCHOMETRIKA
[2]  
[Anonymous], 2000, J SOC STRUCT
[3]  
BALZER M, 2007, P 2007 6 INT AS PAC, pc1
[4]  
Bertin J., 1983, SEMIOLOGY GRAPHICS D
[5]  
Brandes U, 2007, LECT NOTES COMPUT SC, V4372, P42
[6]   GRAPH DRAWING BY FORCE-DIRECTED PLACEMENT [J].
FRUCHTERMAN, TMJ ;
REINGOLD, EM .
SOFTWARE-PRACTICE & EXPERIENCE, 1991, 21 (11) :1129-1164
[7]  
Henning M.y., 2012, Studying Social Networks
[8]   AN ALGORITHM FOR DRAWING GENERAL UNDIRECTED GRAPHS [J].
KAMADA, T ;
KAWAI, S .
INFORMATION PROCESSING LETTERS, 1989, 31 (01) :7-15
[9]  
Lodge Milton., 1981, MAGNITUDE SCALING QU
[10]   AUTOMATING THE DESIGN OF GRAPHICAL PRESENTATIONS OF RELATIONAL INFORMATION [J].
MACKINLAY, J .
ACM TRANSACTIONS ON GRAPHICS, 1986, 5 (02) :110-141