Measuring the movement of a research paradigm

Chaomei Chen

Research output: Contribution to journalConference articlepeer-review

19 Citations (Scopus)


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.

Original languageEnglish
Article number42
Pages (from-to)63-76
Number of pages14
JournalProceedings of SPIE - The International Society for Optical Engineering
Publication statusPublished - 2005
EventProceedings of SPIE-IS and T Electronic Imaging - Visualization and Data Analysis 2005 - San Jose, CA, United States
Duration: 2005 Jan 172005 Jan 18

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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