Conference proceeding
The centrality of pivotal points in the evolution of scientific networks
Proceedings of the 10th international conference on intelligent user interfaces, pp 98-105
10 Jan 2005
Featured in Collection : UN Sustainable Development Goals @ Drexel
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.
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Details
- Title
- The centrality of pivotal points in the evolution of scientific networks
- Creators
- Chaomei Chen
- Publication Details
- Proceedings of the 10th international conference on intelligent user interfaces, pp 98-105
- Conference
- 10th international conference on intelligent user interfaces, 10th
- Series
- IUI '05
- Publisher
- Association for Computing Machinery (ACM)
- Number of pages
- 1
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000231815200015
- Scopus ID
- 2-s2.0-33644593248
- Other Identifier
- 991014878074504721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Theory & Methods
- Telecommunications