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Disruptive papers published in Scientometrics: meaningful results by using an improved variant of the disruption index originally proposed by Wu, Wang, and Evans (2019)

Scientometrics(2020)10.1007/s11192-020-03406-8Source: DataRank Database

Disruptive papers published in Scientometrics: meaningful results by using an improved variant of the disruption index originally proposed by Wu, Wang, and Evans (2019) is a research paper published in Scientometrics (2020). On theSindex it has a DataRank of 2.0. It has been cited 50 times, with 41 citing works in its 1-hop citation network.

N/A
2.0DataRank · unranked
2.0
Open Access50 citations · base score 3.9
Cite:
datarank_citation_only_1hop_v6· scope data_onlyMethodology

Abstract

AbstractWu et al. (Nature 566:378–382, 2019) introduced a new indicator measuring disruption ($${DI}_{1}$$DI1). Bornmann et al. (Do disruption index indicators measure what they propose to measure? The comparison of several indicator variants with assessments by peers, 2019. https://arxiv.org/abs/1911.08775) compared variants of the disruption index and pointed to $${DI}_{5}$$DI5 as an interesting variant. The calculation of a field-specific version of $${DI}_{5}$$DI5 (focusing on disruptiveness within the same field) for Scientometrics papers in the current study reveals that the variant is possibly able to identify landmark papers in scientometrics. This result is in contrast to the Scientometrics analysis previously published by Bornmann and Tekles (Scientometrics 120(1):331–336, 2019) based on the original disruption index ($${DI}_{1}$$DI1).

Data sources & pipeline
Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring
Enrichment:Pending

FAIR Checklist

Context only (not used in score)
Findable (1/2)
  • Has DOI
Accessible (1/2)
  • Open Access
Interoperable (0/2)
    Reusable (0/3)

      FAIR checklist signals are shown for context only and do not affect DataRank scoring.

      DataRank Breakdown

      Base Score 29%Citation Network 71%

      Base Score Contribution

      0.590

      From this paper's citation signal

      Citation Network Contribution

      1.4

      From 35 citing papers with measurable signal

      Learn more about DataRank methodology →

      Top 5 citers driving the network score

      Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.

      Why this DataRank?

      DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 29% comes from its base citations and 71% from the citation network (35 citing papers contributed measurable signal).

      Base score B(p)
      log1p(citation_count) — grows sub-linearly, so a paper with 1,000 citations is not 10× a paper with 100.
      Network N(p)
      Σ over citers of log1p(Cq) ÷ max(outdegreeq, 1). Being cited by a highly-cited paper with few references counts most.
      Damping factor d = 0.85
      DataRank = (1−d)·B(p) + d·N(p) — the two cards above are each already multiplied by their share.
      Self-citations excluded
      Citers sharing any OpenAlex author ID with this paper are filtered out before the network sum.

      Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.

      Read the full methodology →

      Click a node to highlight its connections. Use scroll to zoom. Drag to pan.

      Node colors:CenterData PaperData + Open AccessNon-dataSelected & links| Node size = percentile rank

      Related Papers (10)

      El Profesional de la Información(2019)
      co-cited
      10.3145/epi.2019.mar.07
      Scientometrics(2019)
      co-citedsame journal
      10.1007/s11192-019-03113-z
      A proposal to revise the disruption index
      N/A
      0.406DataRank · unranked
      El profesional de la información(2021)
      co-cited
      10.3145/epi.2021.ene.21