Who are the 100 largest scientific publishers by journal count? A webscraping approach

Nishikawa-Pacher, Andreas

doi:10.1108/jd-04-2022-0083

Cited by 29 publications

(10 citation statements)

References 44 publications

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“…We utilized the list in Nishikawa-Pacher’s study, which identified and ranked the top 100 publishers by number of affiliated journals in their portfolio. 23 The largest publisher on the list produced 3763 journals, and the smallest publisher produced 76 journals. In total, these 100 publishers are responsible for the publication of 28 060 journals.…”

Section: Methodsmentioning

confidence: 99%

Publishers’ and journals’ instructions to authors on use of generative artificial intelligence in academic and scientific publishing: bibliometric analysis

Ganjavi,

Eppler,

Pekcan

et al. 2024

BMJ

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Objectives To determine the extent and content of academic publishers’ and scientific journals’ guidance for authors on the use of generative artificial intelligence (GAI). Design Cross sectional, bibliometric study. Setting Websites of academic publishers and scientific journals, screened on 19-20 May 2023, with the search updated on 8-9 October 2023. Participants Top 100 largest academic publishers and top 100 highly ranked scientific journals, regardless of subject, language, or country of origin. Publishers were identified by the total number of journals in their portfolio, and journals were identified through the Scimago journal rank using the Hirsch index (H index) as an indicator of journal productivity and impact. Main outcome measures The primary outcomes were the content of GAI guidelines listed on the websites of the top 100 academic publishers and scientific journals, and the consistency of guidance between the publishers and their affiliated journals. Results Among the top 100 largest publishers, 24% provided guidance on the use of GAI, of which 15 (63%) were among the top 25 publishers. Among the top 100 highly ranked journals, 87% provided guidance on GAI. Of the publishers and journals with guidelines, the inclusion of GAI as an author was prohibited in 96% and 98%, respectively. Only one journal (1%) explicitly prohibited the use of GAI in the generation of a manuscript, and two (8%) publishers and 19 (22%) journals indicated that their guidelines exclusively applied to the writing process. When disclosing the use of GAI, 75% of publishers and 43% of journals included specific disclosure criteria. Where to disclose the use of GAI varied, including in the methods or acknowledgments, in the cover letter, or in a new section. Variability was also found in how to access GAI guidelines shared between journals and publishers. GAI guidelines in 12 journals directly conflicted with those developed by the publishers. The guidelines developed by top medical journals were broadly similar to those of academic journals. Conclusions Guidelines by some top publishers and journals on the use of GAI by authors are lacking. Among those that provided guidelines, the allowable uses of GAI and how it should be disclosed varied substantially, with this heterogeneity persisting in some instances among affiliated publishers and journals. Lack of standardization places a burden on authors and could limit the effectiveness of the regulations. As GAI continues to grow in popularity, standardized guidelines to protect the integrity of scientific output are needed.

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Section: Methodsmentioning

confidence: 99%

Publishers’ and journals’ instructions to authors on use of generative artificial intelligence in academic and scientific publishing: bibliometric analysis

Ganjavi,

Eppler,

Pekcan

et al. 2024

BMJ

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“…So, such corporations, companies and publishers would be directly affected by RTBF, and subjected to these laws. We note here that two large OA publishers, MDPI and Frontiers (Nishikawa‐Pacher, 2022), are located in Switzerland, which is not in the European Union. Therefore, GDPR does not apply in Switzerland but does apply to Swiss corporations that operate in EEA countries, as occurs with these two publishers.…”

Section: Crossing the Bridge Between Rtbf And Academia: Do Rtbf Princ...mentioning

confidence: 91%

Can the principle of the ‘right to be forgotten’ be applied to academic publishing? Probe from the perspective of personal rights, archival science, open science and post‐publication peer review

Teixeira da Silva,

Nazarovets

2023

Learned Publishing

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In this paper, we reflect on how the principle of the ‘right to be forgotten’ (RTBF), specifically the right to erasure as enshrined in Article 17 (and to some extent Art. 19 and Art. 21) of the General Data Protection Regulation (GDPR; Regulation (EU) 2016/679), or the right to delete undesirable, unflattering or reputation‐damaging archived records of oneself from search engines or databases, might apply to academic publishing. In particular, we focus on archival (library and information) science, post‐publication peer review, and reflect on whether RTBF is compatible with open science principles. Even though RTBF became enshrined in EU law in 2018, its trans‐Atlantic export to the United States faces resistance because it is seen as being incompatible with First Amendment rights. We ponder the pertinence of the debate regarding local versus global applicability of RTBF when considering the transnational nature of some collaborative research. Although RTBF applies broadly to search engines such as Google, we question whether authors have this right and also whether publishers are subjected to this law with respect to science databases, or even ‘local’ (i.e., publisher‐controlled) archives, especially in the light of retractions or withdrawals, in which data and files are removed from a preprint or journal's website or, in extreme cases, where all or most bibliometric information is scrubbed clean, as in the case of ‘silent retractions’. We extend our reflections further to appreciate whether authors or editors are entitled to RTBF in extreme instances of misconduct or fraud. The fundamental right to privacy and personal choice, as is suggested by (or enshrined in) RTBF, is not—in our view—compatible with several principles related to the integrity of data and information, or even their preservation, and may be diametrically opposed, depending on the situation. We encourage wider debate on this budding pertinent issue as a fundamental aspect of academic rights and freedoms.

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“…To identify policies to be analysed, existing lists and rankings of academic publishers found online ( Nishikawa-Pacher, 2022 ; Wikipedia, 2023 ) were combined to form a master list of academic publishers which would be investigated. These publishers included traditional scholarly publishers, preprint servers, university publishing houses, general book publishers, newspapers, academic integrity focus groups, and NGOs.…”

Section: Methodsmentioning

confidence: 99%

Academic publisher guidelines on AI usage: A ChatGPT supported thematic analysis

Perkins,

Roe

2024

F1000Res

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Background As Artificial Intelligence (AI) technologies such as Generative AI (GenAI) have become more common in academic settings, it is necessary to examine how these tools interact with issues of authorship, academic integrity, and research methodologies. The current landscape lacks cohesive policies and guidelines for regulating AI’s role in academic research which has prompted discussions among publishers, authors, and institutions. Methods This study employs inductive thematic analysis to explore publisher policies regarding AI-assisted authorship and academic work. Our methods involved a two-fold analysis using both AI-assisted and traditional unassisted techniques to examine the available policies from leading academic publishers and other publishing or academic entities. The framework was designed to offer multiple perspectives, harnessing the strengths of AI for pattern recognition while leveraging human expertise for nuanced interpretation. The results of these two analyses are combined to form the final themes. Results Our findings indicate six overall themes, three of which were independently identified in both the AI-assisted and unassisted, manual analysis using common software tools. A broad consensus appears among publishers that human authorship remains paramount and that the use of GenAI tools is permissible but must be disclosed. However, GenAI tools are increasingly acknowledged for their supportive roles, including text generation and data analysis. The study also discusses the inherent limitations and biases of AI-assisted analysis, necessitating rigorous scrutiny by authors, reviewers, and editors. Conclusions There is a growing recognition of AI’s role as a valuable auxiliary tool in academic research, but one that comes with caveats pertaining to integrity, accountability, and interpretive limitations. This study used a novel analysis supported by GenAI tools to identify themes emerging in the policy landscape, underscoring the need for an informed, flexible approach to policy formulation that can adapt to the rapidly evolving landscape of AI technologies.

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Who are the 100 largest scientific publishers by journal count? A webscraping approach

Cited by 29 publications

References 44 publications

Publishers’ and journals’ instructions to authors on use of generative artificial intelligence in academic and scientific publishing: bibliometric analysis

Publishers’ and journals’ instructions to authors on use of generative artificial intelligence in academic and scientific publishing: bibliometric analysis

Can the principle of the ‘right to be forgotten’ be applied to academic publishing? Probe from the perspective of personal rights, archival science, open science and post‐publication peer review

Academic publisher guidelines on AI usage: A ChatGPT supported thematic analysis

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