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ResourcesResearch IntegrityDetecting Hijacked Journals by Using Classification Algorithms (Papers: Mona Andoohgin Shahri, et al | 2017)

Australasian Human Research Ethics Consultancy Services Pty Ltd (AHRECS)

Detecting Hijacked Journals by Using Classification Algorithms (Papers: Mona Andoohgin Shahri, et al | 2017)

Published/Released on April 10, 2017 | Posted by Admin on June 26, 2017 / , , , , , ,
 


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Abstract

The grim and thoroughly depressing reality is that all researchers (whatever their level of experience) needs to be sleuth and sceptic in the selection of a publisher. Sadly it is not hard to find awful accounts of outputs wasted, exorbitant fees charged or reputations unfairly tarnished.

Invalid journals are recent challenges in the academic world and many researchers are unacquainted with the phenomenon. The number of victims appears to be accelerating. Researchers might be suspicious of predatory journals because they have unfamiliar names, but hijacked journals are imitations of well-known, reputable journals whose websites have been hijacked. Hijacked journals issue calls for papers via generally laudatory emails that delude researchers into paying exorbitant page charges for publication in a nonexistent journal. This paper presents a method for detecting hijacked journals by using a classification algorithm. The number of published articles exposing hijacked journals is limited and most of them use simple techniques that are limited to specific journals. Hence we needed to amass Internet addresses and pertinent data for analyzing this type of attack. We inspected the websites of 104 scientific journals by using a classification algorithm that used criteria common to reputable journals. We then prepared a decision tree that we used to test five journals we knew were authentic and five we knew were hijacked.
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Keywords
Hijacked journals, Internet fraud, Academic ethics, Editorial process, Spam emails
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Andoohgin Shahri M, Jazi MD, Borchardt G. et al (2017)  Detecting Hijacked Journals by Using Classification Algorithms. Science and Engineering Ethics. doi:10.1007/s11948-017-9914-2
Publisher: https://link.springer.com/article/10.1007%2Fs11948-017-9914-2



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