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

IF 3.1 Q2 PHARMACOLOGY & PHARMACY Advanced pharmaceutical bulletin Pub Date : 2024-07-01 Epub Date: 2024-03-02 DOI:10.34172/apb.2024.029

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

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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.

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揭开隐藏威胁的面纱：对被劫持医学期刊的主题建模分析。

目的：如今，许多研究都在讨论学术出版和相关挑战，但却忽视了期刊被劫持的问题。被劫持期刊是模仿原始期刊的克隆网站，但由网络犯罪分子管理。本研究采用主题建模法分析被劫持版医学期刊上发表的论文：方法：从医学领域的 21 种被劫持期刊中下载了共计 3384 篇论文，并通过主题建模算法进行分析：结果表明，被劫持的医学期刊发表的论文涉及医学领域的大部分领域，并且通常尊重原期刊的主要领域：结论：学术界面临着第三代劫持期刊，对它们的检测可能比普通期刊更复杂。使用人工智能（AI）是应对这一现象的有力工具。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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