Time-Bound Investigational Text Analysis of Predatory E-mails Using Pareto Principle

Predatory act in the scientific field is a progressively growing problem that impacts the integrity of the scientific community. While there are several guidelines available to avoid them, young researchers and inexperienced scientists may not come across them unless it is too late. This might be a challenge, especially for those working in the non-academic sector where a lack of clear guide or reference is not uncommon. The objective of this work is to provide a simple and straightforward guide for recognizing predatory patterns through simple and commercial tools in the analysis of the messages which are used as traps to bring the victims into the net of the intruders ruining the efforts of the researchers and destroying their reputation, in addition to the adverse effects on the progression of their career. The E-mail of an industrial researcher was screened for spam messages for those with scientific nature and then they were isolated in an Excel sheet for processing using the MeaningCloud Add-in platform for text analysis followed by further examination using Pareto charting for prioritization of the contributors using Minitab and Excel. Predatory e-mail senders showed an encouraging pattern to the victims with a systematized insistent attack on the inbox. They hide under the general scope of science, even claiming specificity and professionality. Positive sentiment tendency is predominant in the predatory texts to drag the victim into involvement actions with the fraudulent. Phishers tend to use a bunch of specific keywords to drag their prey to their traps with apparently unprofessional messages that could be sighted through text messages.