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Process / pipelineEmerging topic and burst detection

Emergence Detection in Bibliometrics

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.

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Sources

  1. Kleinberg, J. (2003). Bursty and hierarchical structure in streams. Data Mining and Knowledge Discovery, 7(4), 373-397. DOI: 10.1023/A:1024940629314
  2. Rotolo, D., Hicks, D., & Martin, B. R. (2015). What is an emerging technology? Research Policy, 44(10), 1827-1843. DOI: 10.1016/j.respol.2015.06.006

How to cite this page

ScholarGate. (2026, June 22). Emergence Detection in Bibliometrics (Emerging Topic / Burst Detection). ScholarGate. https://scholargate.app/en/science-technology-studies/emergence-detection-bibliometrics

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ScholarGateEmergence Detection in Bibliometrics (Emergence Detection in Bibliometrics (Emerging Topic / Burst Detection)). Retrieved 2026-06-24 from https://scholargate.app/en/science-technology-studies/emergence-detection-bibliometrics · Dataset: https://doi.org/10.5281/zenodo.20539026