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Proceedings Paper

Measuring the movement of a research paradigm
Author(s): Chaomei Chen
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Paper Abstract

A research paradigm is a dynamical system of scientific works, including their perceived values by peer scientists, and governed by intrinsic intellectual values and associated citation endurance and decay. Identifying an emerging research paradigm and monitoring changes in an existing paradigm have been a challenging task due to the scale and complexity involved. In this article, we describe an exploratory data analysis method for identifying a research paradigm based on clustering scientific articles by their citation half life and betweenness centrality as well as citation frequencies. The Expectation Maximization algorithm is used to cluster articles based on these attributes. It is hypothesized that the resultant clusters correspond to dynamic groupings of articles manifested by a research paradigm. The method is tested with three example datasets: Social Network Analysis (1992-2004), Mass Extinction (1981-2004), and Terrorism (1989-2004). All these subject domains have known emergent paradigms identified independently. The resultant clusters are interpreted and assessed with reference to clusters identified by co-citation links. The consistency and discrepancy between the EM clusters and the link-based co-citation clusters are also discussed.

Paper Details

Date Published: 11 March 2005
PDF: 14 pages
Proc. SPIE 5669, Visualization and Data Analysis 2005, (11 March 2005); doi: 10.1117/12.602251
Show Author Affiliations
Chaomei Chen, Drexel Univ. (United States)

Published in SPIE Proceedings Vol. 5669:
Visualization and Data Analysis 2005
Robert F. Erbacher; Jonathan C. Roberts; Matti T. Grohn; Katy Borner, Editor(s)

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