Evidence map›Paper›PMID 39206400›Full record

ArticleAdvanced pharmaceutical bulletin2024

Unveiling the Hidden Menace: A Topic Modeling Analysis of Hijacked Medical Journals.

Mehdi Dadkhah, Mihály Hegedűs, Prema Nedungadi, Raghu Raman, Lóránt Dénes Dávid

Abstract readEditorial
PubMed Full text at PMC Publisher
In one paragraph

Article in Advanced pharmaceutical bulletin, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Mehdi DadkhahAmrita School of Engineering, Amrita Vishwa Vidyapeetham, Amritapuri, Kerala, India.ORCID https://orcid.org/0000-0001-7964-4762
Mihály HegedűsTomori Pál College, Chamber of Hungarian Auditors, Budapest, Hungary.ORCID https://orcid.org/0000-0001-8064-0208
Prema NedungadiAmrita School of Computing, Amrita Vishwa Vidyapeetham, Amritapuri, Kerala, India.ORCID https://orcid.org/0000-0001-8774-3541
Raghu RamanAmrita School of Business, Amrita Vishwa Vidyapeetham, Amritapuri, Kerala, India.ORCID https://orcid.org/0000-0002-0851-9742
Lóránt Dénes DávidJohn von Neumann University, Faculty of Economics and Business, Department of Tourism and Hospitality, HU-6000 Kecskemét, Hungary.ORCID https://orcid.org/0000-0001-7880-9860

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Nowadays, many studies discuss scholarly publishing and associated challenges, but the problem of hijacked journals has been neglected. Hijacked journals are cloned websites that mimic original journals but are managed by cybercriminals. The present study uses a topic modeling approach to analyze published papers in hijacked versions of medical journals. Methods: A total of 3384 papers were downloaded from 21 hijacked journals in the medical domain and analyzed by topic modeling algorithm. Results: Results indicate that hijacked versions of medical journals are published in most fields of the medical domain and typically respect the primary domain of the original journal. Conclusion: The academic world is faced with the third-generation of hijacked journals, and their detection may be more complex than common ones. The usage of artificial intelligence (AI) can be a powerful tool to deal with the phenomenon.

Indexed as

Hijacked journalsMedicinePredatory journalsScience integrityTopic modeling

Identifiers

PMID39206400
PMCPMC11347746

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.