Automating the design of graphical presentations of relational information
ACM Transactions on Graphics (TOG)
Graph drawing by force-directed placement
Software—Practice & Experience
Graph Drawing: Algorithms for the Visualization of Graphs
Graph Drawing: Algorithms for the Visualization of Graphs
A Comparison of the Readability of Graphs Using Node-Link and Matrix-Based Representations
INFOVIS '04 Proceedings of the IEEE Symposium on Information Visualization
Interactive Visualization of Small World Graphs
INFOVIS '04 Proceedings of the IEEE Symposium on Information Visualization
Visualisation and Analysis of Network Motifs
IV '05 Proceedings of the Ninth International Conference on Information Visualisation
Visual exploration of multivariate graphs
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
The political blogosphere and the 2004 U.S. election: divided they blog
Proceedings of the 3rd international workshop on Link discovery
Coordinated perspectives and enhanced force-directed layout for the analysis of network motifs
APVis '06 Proceedings of the 2006 Asia-Pacific Symposium on Information Visualisation - Volume 60
Task taxonomy for graph visualization
Proceedings of the 2006 AVI workshop on BEyond time and errors: novel evaluation methods for information visualization
ASK-GraphView: A Large Scale Graph Visualization System
IEEE Transactions on Visualization and Computer Graphics
MatrixExplorer: a Dual-Representation System to Explore Social Networks
IEEE Transactions on Visualization and Computer Graphics
Network Visualization by Semantic Substrates
IEEE Transactions on Visualization and Computer Graphics
The worst-case time complexity for generating all maximal cliques and computational experiments
Theoretical Computer Science - Computing and combinatorics
Graph summarization with bounded error
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Analyzing (social media) networks with NodeXL
Proceedings of the fourth international conference on Communities and technologies
ManyNets: an interface for multiple network analysis and visualization
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Network motif discovery using subgraph enumeration and symmetry-breaking
RECOMB'07 Proceedings of the 11th annual international conference on Research in computational molecular biology
MatLink: enhanced matrix visualization for analyzing social networks
INTERACT'07 Proceedings of the 11th IFIP TC 13 international conference on Human-computer interaction - Volume Part II
Analyzing Social Media Networks with NodeXL: Insights from a Connected World
Analyzing Social Media Networks with NodeXL: Insights from a Connected World
Listing all maximal cliques in large sparse real-world graphs
SEA'11 Proceedings of the 10th international conference on Experimental algorithms
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Visual spam campaigns analysis using abstract graphs representation
Proceedings of the Ninth International Symposium on Visualization for Cyber Security
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Analyzing networks involves understanding the complex relationships between entities, as well as any attributes they may have. The widely used node-link diagrams excel at this task, but many are difficult to extract meaning from because of the inherent complexity of the relationships and limited screen space. To help address this problem we introduce a technique called motif simplification, in which common patterns of nodes and links are replaced with compact and meaningful glyphs. Well-designed glyphs have several benefits: they (1) require less screen space and layout effort, (2) are easier to understand in the context of the network, (3) can reveal otherwise hidden relationships, and (4) preserve as much underlying information as possible. We tackle three frequently occurring and high-payoff motifs: fans of nodes with a single neighbor, connectors that link a set of anchor nodes, and cliques of completely connected nodes. We contribute design guidelines for motif glyphs; example glyphs for the fan, connector, and clique motifs; algorithms for detecting these motifs; a free and open source reference implementation; and results from a controlled study of 36 participants that demonstrates the effectiveness of motif simplification.