Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userThe Evolving Ecosystem of Predatory Journals: A Case Study in Indian Perspective
84
0
0.0
(
0
)
Added by
Mayank Singh
Publication date
2019
fields
Informatics Engineering
and research's language is
English
Ask ChatGPT about the research
No Arabic abstract
Digital advancement in scholarly repositories has led to the emergence of a large number of open access predatory publishers that charge high article processing fees from authors but fail to provide necessary editorial and publishing services. Identifying and blacklisting such publishers has remained a research challenge due to the highly volatile scholarly publishing ecosystem. This paper presents a data-driven approach to study how potential predatory publishers are evolving and bypassing several regularity constraints. We empirically show the close resemblance of predatory publishers against reputed publishing groups. In addition to verifying standard constraints, we also propose distinctive signals gathered from network-centric properties to understand this evolving ecosystem better.
rate research
Read More
This study compares the lexical structure of articles titles and abstracts of two extremes in MB (management-business research): the AMJ (Academy of Management Journal), one of its most revered periodicals, and Espacios, the one that unveiled a structural problem in Latin-American MB. Results showed significant differences in the median of titles length and abstracts readability and diversity as AMJ titles length was longer and abstracts both more diverse and readability-demanding.
68 -
Tatiana Savina
, Ivan Sterligov (National Research University Highern School of Economics
, Moscow
2020
We present the results of a large-scale study of potentially predatory journals (PPJ) represented in the Scopus database, which is widely used for research evaluation. Both journal metrics and country, disciplinary data have been evaluated for different groups of PPJ: those listed by Jeffrey Beall and those delisted by Scopus because of publication concerns. Our results show that even after years of delisting, PPJ are still highly visible in the Scopus database with hundreds of active potentially predatory journals. PPJ papers are continuously produced by all major countries, but with different shares. All major subject areas are affected. The largest number of PPJ papers are in engineering and medicine. On average, PPJ have much lower citation metrics than other Scopus-indexed journals. We conclude with a brief survey of the case of Kazakhstan where the share of PPJ papers at one time amounted to almost a half of all Kazakhstan papers in Scopus, and propose a link between PPJ share and national research evaluation policies (in particular, rules of awarding academic degrees). The progress of potentially predatory journal research will be increasingly important because such evaluation methods are becoming more widespread in times of the Metric Tide.
Scientific knowledge cannot be seen as a set of isolated fields, but as a highly connected network. Understanding how research areas are connected is of paramount importance for adequately allocating funding and human resources (e.g., assembling teams to tackle multidisciplinary problems). The relationship between disciplines can be drawn from data on the trajectory of individual scientists, as researchers often make contributions in a small set of interrelated areas. Two recent works propose methods for creating research maps from scientists publication records: by using a frequentist approach to create a transition probability matrix; and by learning embeddings (vector representations). Surprisingly, these models were evaluated on different datasets and have never been compared in the literature. In this work, we compare both models in a systematic way, using a large dataset of publication records from Brazilian researchers. We evaluate these models ability to predict whether a given entity (scientist, institution or region) will enter a new field w.r.t. the area under the ROC curve. Moreover, we analyze how sensitive each method is to the number of publications and the number of fields associated to one entity. Last, we conduct a case study to showcase how these models can be used to characterize science dynamics in the context of Brazil.
Peer-review system has long been relied upon for bringing quality research to the notice of the scientific community and also preventing flawed research from entering into the literature. The need for the peer-review system has often been debated as in numerous cases it has failed in its task and in most of these cases editors and the reviewers were thought to be responsible for not being able to correctly judge the quality of the work. This raises a question Can the peer-review system be improved? Since editors and reviewers are the most important pillars of a reviewing system, we in this work, attempt to address a related question - given the editing/reviewing history of the editors or re- viewers can we identify the under-performing ones?, with citations received by the edited/reviewed papers being used as proxy for quantifying performance. We term such review- ers and editors as anomalous and we believe identifying and removing them shall improve the performance of the peer- review system. Using a massive dataset of Journal of High Energy Physics (JHEP) consisting of 29k papers submitted between 1997 and 2015 with 95 editors and 4035 reviewers and their review history, we identify several factors which point to anomalous behavior of referees and editors. In fact the anomalous editors and reviewers account for 26.8% and 14.5% of the total editors and reviewers respectively and for most of these anomalous reviewers the performance degrades alarmingly over time.
In the same way ecosystems tend to increase maturity by decreasing the flow of energy per unit biomass, we should move towards a more mature science by publishing less but high-quality papers and getting away from joining large teams in small roles. That is, we should decrease our scientific productivity for good.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
