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The centrality of pivotal points in the evolution of scientific Networks
Please use this identifier to cite or link to this item:
http://hdl.handle.net/1860/910
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| Title: | The centrality of pivotal points in the evolution of scientific Networks |
| Authors: | Chen, Chaomei |
| Issue Date: | Jan-2005 |
| Publisher: | Association for Computing Machinery |
| Citation: | 10th International Conference on Intelligent User Interfaces (IUI 2005), (San Diego, CA, January 9-12, 2005), ACM Press, pp. 98-105. Retrieved 6/21/2006 from http://www.pages.drexel.edu/~cc345/papers/iui2005.pdf. |
| Abstract: | In this paper, we describe the development of CiteSpace as an
integrated environment for identifying and tracking thematic
trends in scientific literature. The goal is to simplify the process
of finding not only highly cited clusters of scientific articles, but
also pivotal points and trails that are likely to characterize
fundamental transitions of a knowledge domain as a whole. The
trails of an advancing research field are captured through a
sequence of snapshots of its intellectual structure over time in the
form of Pathfinder networks. These networks are subsequently
merged with a localized pruning algorithm. Pivotal points in the
merged network are algorithmically identified and visualized
using the betweenness centrality metric. An example of finding
clinical evidence associated with reducing risks of heart diseases
is included to illustrate how CiteSpace could be used. The
contribution of the work is its integration of various change
detection algorithms and interactive visualization capabilities to
simply users’ tasks. |
| URI: | http://hdl.handle.net/1860/910 |
| Appears in Collections: | Faculty Research and Publications (IST)
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