Comparer des méthodes

	Emergence Detection in Bibliometrics	Analyse par co-occurrence de mots
Domaine	Science Technology Studies	Scientométrie
Famille	Process / pipeline	Process / pipeline
Année d'origine	2003	1983
Auteur d'origine	Jon Kleinberg (burst detection); Daniele Rotolo, Diana Hicks & Ben Martin (emerging-technology criteria)	Michel Callon, Jean-Pierre Courtial, and colleagues
Type	Bibliometric / text-mining detection pipeline	Scientometric network analysis technique
Source fondatrice	Kleinberg, J. (2003). Bursty and hierarchical structure in streams. Data Mining and Knowledge Discovery, 7(4), 373-397.	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.
Alias	Emerging topic detection, Burst detection in bibliometrics, Emerging technology detection	keyword co-occurrence analysis, co-word mapping, keyword co-word network, CWA
Apparentées	4	6
Résumé	Emergence detection in bibliometrics is a family of text-mining and bibliometric methods for spotting emerging research topics and technologies early, by analysing the dynamics of terms, citations, and references in publication streams. It combines burst-detection algorithms that flag sudden surges in usage with operational criteria for what makes a topic genuinely 'emerging', turning large scholarly corpora into early signals of scientific and technological change.	Co-word analysis is a scientometric technique that quantifies how often pairs of keywords, subject terms, or title words appear together across a corpus of publications. By treating simultaneous occurrence as a proxy for conceptual relatedness, it constructs networks and clusters that reveal the intellectual structure, dominant themes, and emerging sub-fields of a research domain.