Étiquette : scientific communication

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EN

Using bibliometrics to detect questionable authorship and affiliation practices and their impact on global research metrics: A case study of 14 universities

Authors : Lokman I. Meho, Elie A. Akl

From 2019 to 2023, a subset of 80 highly published universities demonstrated research output increases exceeding 100%, compared to the global average of 20%. Among these, 14 institutions showed significant declines in first authorship rates, raising questions about their authorship and affiliation practices.

This study employed bibliometric analysis to examine shifts in authorship and affiliation dynamics at these universities. Key findings include a 234% rise in total publications, a 23 percentage point drop in first authorship rates, and an increase in hyper-prolific authors from 23 to 177. International collaborations surged, and several universities exhibited sharp rises in multiaffiliated publications. Additionally, the proportion of articles published in top 10% journals increased by 11 percentage points, and the proportion of articles ranked among the world’s top 10% most cited grew by 12 percentage points.

These trends raise concerns about the integrity of authorship and affiliation practices as they deviate from normative behavior, far exceeding those observed nationally and at top-ranked universities—Caltech, MIT, Princeton, and UC Berkeley.

The study emphasizes the need for collaborative reforms by universities, ranking agencies, publishers, and other entities, highlighting the importance of each entity’s role in preserving academic integrity and ensuring the reliability of global research metrics.

URL : Using bibliometrics to detect questionable authorship and affiliation practices and their impact on global research metrics: A case study of 14 universities

DOI : https://doi.org/10.1162/qss_a_00339

Catégories
EN

Evaluating the linguistic coverage of OpenAlex: An assessment of metadata accuracy and completeness

Authors : Lucía Céspedes, Diego Kozlowski, Carolina Pradier, Maxime Holmberg Sainte-Marie, Natsumi Solange Shokida, Pierre Benz,
Constance Poitras, Anton Boudreau Ninkov, Saeideh Ebrahimy, Philips Ayeni, Sarra Filali, Bing Li, Vincent Larivière

Clarivate’s Web of Science (WoS) and Elsevier’s Scopus have been for decades the main sources of bibliometric information. Although highly curated, these closed, proprietary databases are largely biased toward English-language publications, underestimating the use of other languages in research dissemination.

Launched in 2022, OpenAlex promised comprehensive, inclusive, and open-source research information. While already in use by scholars and research institutions, the quality of its metadata is currently still being assessed. This paper contributes to this literature by assessing the completeness and accuracy of OpenAlex’s metadata related to language, through a comparison with WoS, as well as an in-depth manual validation of a sample of 6836 articles.

Results show that OpenAlex exhibits a far more balanced linguistic coverage than WoS. However, language metadata are not always accurate, which leads OpenAlex to overestimate the place of English while underestimating that of other languages. If used critically, OpenAlex can provide comprehensive and representative analyses of languages used for scholarly publishing, but more work is needed at infrastructural level to ensure the quality of metadata on language.

URL : Evaluating the linguistic coverage of OpenAlex: An assessment of metadata accuracy and completeness

DOI : https://doi.org/10.1002/asi.24979

Catégories
EN

Sustaining the “frozen footprints” of scholarly communication through open citations

Author : Zehra Taşkın

This review examines the role of open citations in fostering transparency, reproducibility, and accessibility in scholarly communication. Through a critical synthesis of diverse sources—articles, proceedings, presentations, datasets, and blog posts—it explores the motivations behind citing, the evolving meanings of citations, and key milestones in the open citation movement. Particular attention is given to initiatives like OpenCitations and the Initiative for Open Citations (I4OC), highlighting their contributions to advancing open scholarship.

Key findings indicate that open citations democratize research by providing free access to citation data, improving discoverability, and facilitating the creation of public citation graphs. Technological advancements, such as advanced data models and reference mining tools, have significantly contributed to the management and utilization of citation data. Despite these benefits, challenges such as ensuring data quality and standardization, addressing structural inequalities in citation networks, and achieving universal publisher adoption persist.

The study concludes with recommendations for future efforts, emphasizing policy advocacy, technological innovation, global collaboration, and educational initiatives to promote the widespread adoption and effective use of open citations. These strategies aim to make the “frozen footprints” of scholarly communication accessible to all, fostering a more equitable and transparent scientific landscape.

URL : Sustaining the “frozen footprints” of scholarly communication through open citations

DOI : https://doi.org/10.1002/asi.24982

Catégories
EN

‘As of my last knowledge update’: How is content generated by ChatGPT infiltrating scientific papers published in premier journals?

Author : Artur Strzelecki

The aim of this paper is to highlight the situation whereby content generated by the large language model ChatGPT is appearing in peer-reviewed papers in journals by recognized publishers. The paper demonstrates how to identify sections that indicate that a text fragment was generated, that is, entirely created, by ChatGPT. To prepare an illustrative compilation of papers that appear in journals indexed in the Web of Science and Scopus databases and possessing Impact Factor and CiteScore indicators, the SPAR4SLR method was used, which is mainly applied in systematic literature reviews.

Three main findings are presented: in highly regarded premier journals, articles appear that bear the hallmarks of the content generated by AI large language models, whose use was not declared by the authors (1); many of these identified papers are already receiving citations from other scientific works, also placed in journals found in scientific databases (2); and, most of the identified papers belong to the disciplines of medicine and computer science, but there are also articles that belong to disciplines such as environmental science, engineering, sociology, education, economics and management (3).

This paper aims to continue and add to the recently initiated discussion on the use of large language models like ChatGPT in the creation of scholarly works.

URL : ‘As of my last knowledge update’: How is content generated by ChatGPT infiltrating scientific papers published in premier journals?

DOI : https://doi.org/10.1002/leap.1650

Catégories
EN

Patent research in academic literature. Landscape and trends with a focus on patent analytics

Authors : Cristian Mejia, Yuya Kajikawa

Patent analytics is crucial for understanding innovation dynamics and technological trends. However, a comprehensive overview of this rapidly evolving field is lacking. This study presents a data-driven analysis of patent research, employing citation network analysis to categorize and examine research clusters. Here, we show that patent research is characterized by interconnected themes spanning fundamental patent systems, indicator development, methodological advancements, intellectual property management practices, and diverse applications.

We reveal central research areas in patent strategies, technological impact, and patent citation research while identifying emerging focuses on environmental sustainability and corporate innovation. The integration of advanced analytical techniques, including AI and machine learning, is observed across various domains. This study provides insights for researchers and practitioners, highlighting opportunities for cross-disciplinary collaboration and future research directions.

URL : Patent research in academic literature. Landscape and trends with a focus on patent analytics

DOI : https://doi.org/10.3389/frma.2024.1484685

Catégories
EN

Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents

Authors : Zeyd Boukhers, Cong Yang

The availability of metadata for scientific documents is pivotal in propelling scientific knowledge forward and for adhering to the FAIR principles (i.e. Findability, Accessibility, Interoperability, and Reusability) of research findings. However, the lack of sufficient metadata in published documents, particularly those from smaller and mid-sized publishers, hinders their accessibility. This issue is widespread in some disciplines, such as the German Social Sciences, where publications often employ diverse templates. To address this challenge, our study evaluates various feature learning and prediction methods, including natural language processing (NLP), computer vision (CV), and multimodal approaches, for extracting metadata from documents with high template variance.

We aim to improve the accessibility of scientific documents and facilitate their wider use. To support our comparison of these methods, we provide comprehensive experimental results, analyzing their accuracy and efficiency in extracting metadata. Additionally, we provide valuable insights into the strengths and weaknesses of various feature learning and prediction methods, which can guide future research in this field.

URL : Comparison of Feature Learning Methods for Metadata Extraction from PDF Scholarly Documents

Arxiv : https://arxiv.org/abs/2501.05082

Catégories
EN

How to build an Open Science Monitor based on publications? A French perspective

Authors : Laetitia Bracco, Eric Jeangirard, Anne L’Hôte, Laurent Romary

Many countries and institutions are striving to develop tools to monitor their open science policies. Since 2018, with the launch of its National Plan for Open Science, France has been progressively implementing a monitoring framework for its public policy, relying exclusively on reliable, open, and controlled data. Currently, this monitoring focuses on research outputs, particularly publications, as well as theses and clinical trials.

Publications serve as a basis for analyzing other dimensions, including research data, code, and software. The metadata associated with publications is therefore particularly valuable, but the methodology for leveraging it raises several challenges. Here, we briefly outline how we have used this metadata to construct the French Open Science Monitor.

URL : How to build an Open Science Monitor based on publications? A French perspective

Arxiv : https://arxiv.org/abs/2501.02856