The centrality of pivotal points in the evolution of scientific networks

Chaomei Chen

Research output: Contribution to conferencePaperpeer-review

74 Citations (Scopus)

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.

Original languageEnglish
Pages98-105
Number of pages8
DOIs
Publication statusPublished - 2005
EventIUI 05 - 2005 International Conference on Intelligent User Interfaces - San Diego, CA, United States
Duration: 2005 Jan 92005 Jan 12

Other

OtherIUI 05 - 2005 International Conference on Intelligent User Interfaces
Country/TerritoryUnited States
CitySan Diego, CA
Period05/1/905/1/12

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction

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