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Area of Science:

  • Bibliometrics
  • Scientometrics
  • Information Science

Background:

  • Understanding the dynamics of scientific fields is crucial for research assessment and funding.
  • Co-citation analysis is a bibliometric technique used to identify relationships between documents and research areas.
  • Tracking the evolution of research fields requires robust methodologies to capture emerging trends.

Purpose of the Study:

  • To investigate the utility of co-citation clusters across time periods for monitoring research area emergence and growth.
  • To develop and apply methods for predicting near-term changes in research fields.
  • To introduce and validate a new metric, 'in-group citation', to address issues with 'single-issue clusters'.

Main Methods:

  • Utilized co-citation clustering on three overlapping six-year data sets (1996-2001, 1997-2002, 1998-2003).
  • Reviewed co-citation clustering, mapping, and string formation methodologies.
  • Defined and applied 'cluster currency' (average age of highly cited papers) and 'in-group citation' metrics.

Main Results:

  • Found a significant association between cluster currency in a prior period and subsequent changes in cluster size and citation frequency.
  • Demonstrated that 'cluster currency' can serve as a predictor for research area dynamics.
  • Showcased the effectiveness of 'in-group citation' in refining the analysis of 'single-issue clusters'.

Conclusions:

  • Co-citation cluster analysis over time effectively tracks the emergence and evolution of research areas.
  • Cluster currency is a valuable indicator for predicting the near-term trajectory of scientific fields.
  • The 'in-group citation' metric enhances the accuracy of bibliometric analysis by mitigating the impact of specialized, narrow research clusters.