ABSTRACT
Scientific fake papers, containing manipulated or completely fabricated data, are a problem that has reached dramatic dimensions. Companies known as paper mills (or more bluntly as "criminal science publishing gangs") produce and sell such fake papers on a large scale. The main drivers of the fake paper flood are the pressure in academic systems and (monetary) incentives to publish in respected scientific journals and sometimes the personal desire for increased "prestige." Published fake papers cause substantial scientific, economic, and social damage. There are numerous information sources that deal with this topic from different points of view. This review aims to provide an overview of these information sources until June 2024. Much more original research with larger datasets is needed, for example on the extent and impact of the fake paper problem and especially on how to detect them, as many findings are based more on small datasets, anecdotal evidence, and assumptions. A long-term solution would be to overcome the mantra of publication metrics for evaluating scientists in academia.
ABSTRACT
Honesty of publications is fundamental in science. Unfortunately, science has an increasing fake paper problem with multiple cases having surfaced in recent years, even in renowned journals. There are companies, the so-called paper mills, which professionally fake research data and papers. However, there is no easy way to systematically identify these papers. Here, we show that scanning for exchanged authors in resubmissions is a simple approach to detect potential fake papers. We investigated 2056 withdrawn or rejected submissions to Naunyn-Schmiedeberg's Archives of Pharmacology (NSAP), 952 of which were subsequently published in other journals. In six cases, the stated authors of the final publications differed by more than two thirds from those named in the submission to NSAP. In four cases, they differed completely. Our results reveal that paper mills take advantage of the fact that journals are unaware of submissions to other journals. Consequently, papers can be submitted multiple times (even simultaneously), and authors can be replaced if they withdraw from their purchased authorship. We suggest that publishers collaborate with each other by sharing titles, authors, and abstracts of their submissions. Doing so would allow the detection of suspicious changes in the authorship of submitted and already published papers. Independently of such collaboration across publishers, every scientific journal can make an important contribution to the integrity of the scientific record by analyzing its own pool of withdrawn and rejected papers versus published papers according to the simple algorithm proposed in the present paper.
Subject(s)
AuthorshipABSTRACT
An increasing fake paper problem is a cause for concern in the scientific community. These papers look scientific but contain manipulated data or are completely fictitious. So-called paper mills produce fake papers on a large scale and publish them in the name of people who buy authorship. The aim of this study was to learn more about the characteristics of fake papers at the metadata level. We also investigated whether some of these characteristics could be used to detect fake papers. For that purpose, we examined metadata of 12 fake papers that were retracted by Naunyn-Schmiedeberg's Archives of Pharmacology (NSAP) in recent years. We also compared many of these metadata with those of a reference group of 733 articles published by NSAP. It turned out that in many characteristics the fake papers we examined did not differ substantially from the other articles. It was only noticeable that the fake papers came almost exclusively from a certain country, used non-institutional email addresses more often than average, and referenced dubious literature significantly more often. However, these three features are only of limited use in identifying fake papers. We were also able to show that fake papers not only contaminate the scientific record while they are unidentified but also continue to do so even after retraction. Our results indicate that fake papers are well made and resemble honest papers even at the metadata level. Because they contaminate the scientific record in the long term and this cannot be fully contained even by their retraction, it is particularly important to identify them before publication. Further research on the topic of fake papers is therefore urgently needed.
