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There are many misleading scientific metrics that are not known to the scientific community, particularly novice researchers. There is limited research in the area of misleading metrics, particularly related to business journals. Therefore, this research aims to examine the use of misleading metrics by business journals, the most popular misleading metrics, and countries contributing to the website traffic for such metrics. We used Scimago ranking for business journals and examined the website of each for the use of misleading metrics. Further, we used a domain-based approach by gathering data from Search Engine Optimization websites (i.e., Alexa and Ubersuggest). Only a few Scopus-indexed, low-quality business journals used misleading metrics on their website. The most common misleading metrics were International Scientific Institute, Open Academic Journals Index, CiteFactor, IndexCopernicus, and International Scientific Indexing. In addition, Indian authors were the most frequent visitors of the websites of misleading metrics. [ABSTRACT FROM AUTHOR]

Predatory journals are continuing to expand across disciplines and target researchers via different media such as websites and spam emails to potential authors. While multiple studies have described characteristics of predatory journals, less research has been on done on authors' perceptions of and experiences with predatory journals. In this paper, by using a data science approach, we developed a tool that analyzes the content of social media and summarizes what users (authors) have shared about predatory journals. This tool is useful in understanding the current concerns of researchers about predatory journals and examining current activities of these journals. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) is a popular technological paradigm offering several promised advantages. IoT has been facing different challenges discussed by various researchers. The available literature on IoT challenges is mostly based on experimental studies or reviews. The analysis of webpages as a valuable database can be a good idea to provide an insight into IoT challenges. Thus, this paper was aimed at providing an overall view of webpages discussing IoT challenges. In this regard, the text mining approach was implemented to analyze the related webpages. The obtained results revealed that challenges relate to the security of IoT devices, connectivity, data processing, and storage have been the most prevalent topics in the selected webpages. [ABSTRACT FROM AUTHOR]

Hijacked journals are cloned websites that resemble the homepages of legitimate journals, whose aim is to collect processing and publication fees from unwary authors. There is a growing recognition that the recent proliferation of these scam sites poses a threat to the integrity of the scientific process. This study presents an approach intended to prevent the indexing of papers published by hijacked journals in scientific databases by using classification algorithms. We will provide an overview of the problem, define key features of hijacked journals, and present a decision tree that can be used to detect hijacked publications. [ABSTRACT FROM PUBLISHER]