Paper Info
Title
Interactive network exploration to derive insights: filtering, clustering, grouping, and simplification
Abstract
The growing importance of network analysis has increased attention on interactive exploration to derive insights and support personal, business, legal, scientific, or national security decisions. Since networks are often complex and cluttered, strategies for effective filtering, clustering, grouping, and simplification are helpful in finding key nodes and links, surprising clusters, important groups, or meaningful patterns. We describe readability metrics and strategies that have been implemented in NodeXL, our free and open source network analysis tool, and show examples from our research. While filtering, clustering, and grouping have been used in many tools, we present several advances on these techniques. We also discuss our recent work on motif simplification, in which common patterns are replaced with compact and meaningful glyphs, thereby improving readability.
Year
DOI
Venue
2012
10.1007/978-3-642-36763-2_2
Graph Drawing
Keywords
Field
DocType
important group,meaningful pattern,key node,readability metrics,interactive exploration,network analysis,meaningful glyphs,interactive network exploration,open source network analysis,common pattern,motif simplification,visual analytics,network visualization
Graph drawing,Glyph,Discrete mathematics,Data mining,Information retrieval,Computer science,Visual analytics,Filter (signal processing),Motif (music),Readability,Network analysis,Cluster analysis
Conference
Citations 
PageRank 
References 
8
0.44
27
Authors
2
Name
Order
Citations
PageRank
Ben Shneiderman1127723081.95
Cody Dunne243727.88