Bibliometrics Methods in Detecting Citations to Questionable Journals

Barrantes, Bárbara S. Lancho; Dalton, Sally; Andre, Deirdre

doi:10.1016/j.acalib.2023.102749

Search citation statements

Order By: Relevance

Paper Sections

Select...

Introduction1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

(1 citation statement)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Identifying predatory publications using checklists of their characteristics has been a significant focus (Beall, 2012, 2013; Cukier, Lalu, et al, 2020; Strinzel et al, 2019; Trejo‐Pech et al, 2021). More recently, bibliometric (Barrantes et al, 2023) and machine learning (Bedmutha & Bedmutha, 2022) approaches have emerged as possible ways to assist editors and authors in avoiding inappropriate referencing.…”

Section: Introductionmentioning

confidence: 99%

Editorial actions taken to reduce publishing references from predatory sources: A case study

Dodgson,

Bamberger,

Haile

et al. 2024

Learned Publishing

View full text Add to dashboard Cite

Key points Our policy and implementation successfully identified references from predatory publishers, which authors without hesitation agreed to remove before publication. Higher predatory reference patterns emerged among authors in low‐income countries, those with non‐English primary languages, and sole authorship. After a year of implementing our policy, the editors changed our policy and workflow to better handle references from predatory publishers cited in literature reviews and meta‐analyses. Editorial responsibility is discussed, particularly concerning support for authors from lower‐ and middle‐income countries.

show abstract