Related papers: Distinguishing articles in questionable and non-qu…
Objectives: Trial registries can be used to measure reporting biases and support systematic reviews but 45% of registrations do not provide a link to the article reporting on the trial. We evaluated the use of document similarity methods to…
Recently, two new indicators (Equalized Mean-based Normalized Proportion Cited, EMNPC; Mean-based Normalized Proportion Cited, MNPC) were proposed which are intended for sparse scientometrics data. The indicators compare the proportion of…
One main challenge in social media is to identify trustworthy information. If we cannot recognize information as trustworthy, that information may become useless or be lost. Opposite, we could consume wrong or fake information with major…
In scholarly publishing, blacklists aim to register fraudulent or deceptive journals and publishers, also known as "predatory", to minimise the spread of unreliable research and the growing of fake publishing outlets. However, blacklisting…
Predatory journals are Open Access journals of highly questionable scientific quality. Such journals pretend to use peer review for quality assurance, and spam academics with requests for submissions, in order to collect author payments. In…
This study provides quantitative evidence on how the use of journal rankings can disadvantage interdisciplinary research in research evaluations. Using publication and citation data, it compares the degree of interdisciplinarity and the…
Recent studies comparing AI-generated and human-authored literary texts have produced conflicting results: some suggest AI already surpasses human quality, while others argue it still falls short. We start from the hypothesis that such…
The large language model (LLM) ChatGPT's quality scores for journal articles correlate more strongly with human judgements than some citation-based indicators in most fields. Averaging multiple ChatGPT scores improves the results,…
Citation information in scholarly data is an important source of insight into the reception of publications and the scholarly discourse. Outcomes of citation analyses and the applicability of citation based machine learning approaches…
The increasingly rapid spread of information about COVID-19 on the web calls for automatic measures of quality assurance. In that context, we check the credibility of news content using selected linguistic features. We present two empirical…
In our chapter we address the statistical analysis of percentiles: How should the citation impact of institutions be compared? In educational and psychological testing, percentiles are already used widely as a standard to evaluate an…
Two journal-level indicators, respectively the mean ($m^i$) and the standard deviation ($v^i$) are proposed to be the core indicators of each journal and we show that quite several other indicators can be calculated from those two core…
As the number of accepted papers at AI and ML conferences reaches into the thousands, it has become unclear how researchers access and read research publications. In this paper, we investigate the role of social media influencers in…
Large Language Models (LLMs) can be helpful for literature search and summarisation, but retracted articles can confuse them. This article asks three open weights (offline) LLMs whether 161 high profile retracted articles had been…
Early in researchers' careers, it is difficult to assess how good their work is or how important or influential the scholars will eventually be. Hence, funding agencies, academic departments, and others often use the Journal Impact Factor…
Quality requirements deal with how well a product should perform the intended functionality, such as start-up time and learnability. Researchers argue they are important and at the same time studies indicate there are deficiencies in…
LLMs offer valuable capabilities, yet they can be utilized by malicious users to disseminate deceptive information and generate fake news. The growing prevalence of LLMs poses difficulties in crafting detection approaches that remain…
Collaborations are an integral part of scientific research and publishing. In the past, access to large-scale corpora has limited the ways in which questions about collaborations could be investigated. However, with improvements in…
The purpose of citation indexes and metrics is intended to be a measure for scientific innovation and quality for researchers, journals, and institutions. However, those metrics are often prone to abuse and manipulation by excessive and…
Quality Estimation (QE) metrics are vital in machine translation for reference-free evaluation and increasingly serve as selection criteria in data filtering and candidate reranking. However, the prevalence and impact of length bias in QE…