Detecting Hijacked Journals by Using Classification Algorithms

  • Mona Andoohgin Shahri
  • Mohammad Davarpanah Jazi
  • Glenn Borchardt
  • Mehdi Dadkhah
Original Paper

Abstract

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.

Keywords

Hijacked journals Internet fraud Academic ethics Editorial process Spam emails 

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Copyright information

© Springer Science+Business Media Dordrecht 2017

Authors and Affiliations

  • Mona Andoohgin Shahri
    • 1
  • Mohammad Davarpanah Jazi
    • 1
  • Glenn Borchardt
    • 2
  • Mehdi Dadkhah
    • 3
  1. 1.Department of Computer and Information TechnologyFoolad Institute of TechnologyFoolad shahrIran
  2. 2.Progressive Science InstituteBerkeleyUSA
  3. 3.Department of Management, Faculty of Economics and Administrative SciencesFerdowsi University of MashhadMashhadIran

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