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Automatic text processing: the transformation, analysis, and retrieval of information by computer
Cone Trees: animated 3D visualizations of hierarchical information
CHI '91 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Pathfinder associative networks: studies in knowledge organization
Pathfinder associative networks: studies in knowledge organization
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Visualizing the evolution of Web ecologies
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Mapping Scientific Frontiers: The Quest for Knowledge Visualization
Mapping Scientific Frontiers: The Quest for Knowledge Visualization
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Journal of the American Society for Information Science and Technology
Journal of the American Society for Information Science and Technology
Botanical Visualization of Huge Hierarchies
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Visual Unrolling of Network Evolution and the Analysis of Dynamic Discourse
INFOVIS '02 Proceedings of the IEEE Symposium on Information Visualization (InfoVis'02)
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HICSS '99 Proceedings of the Thirty-Second Annual Hawaii International Conference on System Sciences-Volume 1 - Volume 1
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A system for visualizing and analyzing the evolution of the web with a time series of graphs
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Graph Signatures for Visual Analytics
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Fast shared-memory algorithms for computing the minimum spanning forest of sparse graphs
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Information Sciences: an International Journal
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KSEM'07 Proceedings of the 2nd international conference on Knowledge science, engineering and management
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Information Visualization
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Information Visualization
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Scientometrics
A study on the locality behavior of minimum spanning tree algorithms
HiPC'06 Proceedings of the 13th international conference on High Performance Computing
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Revealing themes and trends in the knowledge domain's intellectual structure
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Visualisation and analysis of large and complex scale-free networks
EUROVIS'05 Proceedings of the Seventh Joint Eurographics / IEEE VGTC conference on Visualization
Centrality based visualization of small world graphs
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Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
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Network evolution is a ubiquitous phenomenon in a wide variety of complex systems. There is an increasing interest in statistically modeling the evolution of complex networks such as small-world networks and scale-free networks. In this article, we address a practical issue concerning the visualization of network evolution. We compare the visualizations of co-citation networks of scientific publications derived by two widely known link reduction algorithms, namely minimum spanning trees (MSTs) and Pathfinder networks (PFNETs). Our primarily goal is to identify the strengths and weaknesses of the two methods in fulfilling the need for visualizing evolving networks. Two criteria are derived for assessing visualizations of evolving networks in terms of topological properties and dynamical properties. We examine the animated visualization models of the evolution of botulinum toxin research in terms of its co-citation structure across a 58-year span (1945-2002). The results suggest that although high-degree nodes dominate the structure of MST models, such structures can be inadequate in depicting the essence of how the network evolves because MST removes potentially significant links from high-order shortest paths. In contrast, PFNET models clearly demonstrate their superiority in maintaining the cohesiveness of some of the most pivotal paths, which in turn make the growth animation more predictable and interpretable. We suggest that the design of visualization and modeling tools for network evolution should take the cohesiveness of critical paths into account.