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.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- Kleinberg, J. (2003). Bursty and hierarchical structure in streams. Data Mining and Knowledge Discovery, 7(4), 373-397. · DOI 10.1023/A:1024940629314
- 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
Curated claims
Claims persisted in the evidence ledger, each with its own assessment.
This view does not invent a claim assessment when the ledger has none.
Related methods
Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.