Conference proceeding
Measuring the movement of a research paradigm
Proceedings of SPIE, v 5669(1), pp 63-76
11 Mar 2005
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:
(1992-2004),
(1981-2004), and
(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.
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Details
- Title
- Measuring the movement of a research paradigm
- Creators
- Chaomei Chen - Drexel University
- Publication Details
- Proceedings of SPIE, v 5669(1), pp 63-76
- Conference
- Visualization and Data Analysis 2005 (2005)
- Publisher
- Society of Photo-Optical Instrumentation Engineers (SPIE)
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000228667300007
- Scopus ID
- 2-s2.0-21944442066
- Other Identifier
- 991019174902804721
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- Web of Science research areas
- Imaging Science & Photographic Technology