Process / pipelineReview / evidence synthesis

Meta-Regression-Based Co-Word Analysis

Meta-regression-based co-word analysis is a hybrid scientometric technique that enriches traditional co-word mapping by weighting keyword co-occurrence networks with meta-regression-derived effect estimates. Instead of treating all documents as equally informative, the method uses statistical regression to incorporate study-level moderators — such as publication year, sample size, or methodological quality — into the co-occurrence structure, revealing how thematic clusters in a research field vary across moderator conditions.

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Sources

  1. Callon, M., Courtial, J. P., Turner, W. A., & Bauin, S. (1983). From translations to problematic networks: An introduction to co-word analysis. Social Science Information, 22(2), 191–235. DOI: 10.1177/053901883022002003
  2. Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package. Journal of Statistical Software, 36(3), 1–48. DOI: 10.18637/jss.v036.i03

Related methods

ScholarGateMeta-Regression-Based Co-Word Analysis (Meta-Regression-Based Co-Word Analysis). Retrieved 2026-06-04 from https://scholargate.app/en/scientometrics/meta-regression-based-co-word-analysis