Process / pipelinesemantic-network

Keyword Co-Occurrence Analysis

Keyword co-occurrence analysis is a text mining and bibliometric method that identifies research themes and their relationships by analyzing how frequently terms or keywords appear together in abstracts, titles, or indexed keywords of scientific publications. When two keywords appear together frequently, they are considered co-occurring, indicating a shared thematic or conceptual relationship. This method rapidly reveals the topical structure of a research field without relying on formal classifications, making it particularly useful for detecting emerging research areas and understanding disciplinary boundaries.

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Sources

  1. Cobo, M. J., López-Herrera, A. G., Herrera-Viedma, E., & Herrera, F. (2011). An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the fuzzy sets theory field. Journal of Informetrics, 5(1), 146–166. DOI: 10.1016/j.joi.2010.10.002
  2. Van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538. DOI: 10.1007/s11192-009-0146-3

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Referenced by

ScholarGateKeyword Co-Occurrence Analysis (Keyword Co-Occurrence Analysis). Retrieved 2026-06-04 from https://scholargate.app/en/bibliometrics/keyword-co-occurrence