Dadkhah Mehdi, Hegedűs Mihály, Nedungadi Prema, Raman Raghu, Dávid Lóránt Dénes
Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Amritapuri, Kerala, India.
Tomori Pál College, Chamber of Hungarian Auditors, Budapest, Hungary.
Adv Pharm Bull. 2024 Jul;14(2):255-261. doi: 10.34172/apb.2024.029. Epub 2024 Mar 2.
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.
A total of 3384 papers were downloaded from 21 hijacked journals in the medical domain and analyzed by topic modeling algorithm.
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.
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.
如今，许多研究都在探讨学术出版及相关挑战，但被劫持期刊的问题却被忽视了。被劫持期刊是克隆网站，它们模仿原期刊，但由网络犯罪分子管理。本研究采用主题建模方法来分析医学期刊被劫持版本中发表的论文。
从21种医学领域的被劫持期刊中总共下载了3384篇论文，并通过主题建模算法进行分析。
结果表明，医学期刊的被劫持版本在医学领域的大多数领域都有发表，并且通常遵循原期刊的主要领域。
学术界面临着第三代被劫持期刊，其检测可能比普通期刊更为复杂。人工智能（AI）的应用可以成为应对这一现象的有力工具。
