Evidence map›Paper›PMID 39700077›Full record

ArticlePloS one2024

Breaking down the relationship between disruption scores and citation counts.

Mingtang Li, Giacomo Livan, Simone Righi

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Mingtang LiDepartment of Computer Science, University College London, London, United Kingdom.
Giacomo LivanDepartment of Computer Science, University College London, London, United Kingdom.
Simone RighiDepartment of Economics "Marco Biagi", University of Modena and Reggio Emilia, Modena, Italy.ORCID 0000-0001-9821-8451

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The emergence of the disruption score provides a new perspective that differs from traditional metrics of citations and novelty in research evaluation. Motivated by current studies on the differences among these metrics, we examine the relationship between disruption scores and citation counts. Intuitively, one would expect disruptive scientific work to be rewarded by high volumes of citations and, symmetrically, impactful work to also be disruptive. A number of recent studies have instead shown that such intuition is often at odds with reality. In this paper, we break down the relationship between impact and disruption with a detailed correlation analysis in two large data sets of publications in Computer Science and Physics. We find that highly disruptive papers tend to receive a higher number of citations than average. Contrastingly, the opposite is not true, as we do not find highly cited papers to be particularly disruptive. Notably, these results qualitatively hold even within individual scientific careers, as we find that-on average-an author's most disruptive work tends to be well cited, whereas their most cited work does not tend to be disruptive. We discuss the implications of our findings in the context of academic evaluation systems, and show how they can contribute to reconcile seemingly contradictory results in the literature.

Indexed as

BibliometricsJournal Impact FactorHumansPublicationsPublishing

Identifiers

PMID39700077
PMCPMC11658639

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.