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Open access improves the dissemination of science: insights from Wikipedia

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Authors : Puyu Yang, Ahad Shoaib, Robert West, Giovanni Colavizza

Wikipedia is a well-known platform for disseminating knowledge, and scientific sources, such as journal articles, play a critical role in supporting its mission. The open access movement aims to make scientific knowledge openly available, and we might intuitively expect open access to help further Wikipedia’s mission. However, the extent of this relationship remains largely unknown.

To fill this gap, we analyse a large dataset of citations from the English Wikipedia and model the role of open access in Wikipedia’s citation patterns. Our findings reveal that Wikipedia relies on open access articles at a higher overall rate (44.1%) compared to their availability in the Web of Science (23.6%) and OpenAlex (22.6%). Furthermore, both the accessibility (open access status) and academic impact (citation count) significantly increase the probability of an article being cited on Wikipedia.

Specifically, open access articles are extensively and increasingly more cited in Wikipedia, as they show an approximately 64.7% higher likelihood of being cited in Wikipedia when compared to paywalled articles, after controlling for confounding factors. This open access citation effect is particularly strong for articles with high citation counts or published in recent years.

Our findings highlight the pivotal role of open access in facilitating the dissemination of scientific knowledge, thereby increasing the likelihood of open access articles reaching a more diverse audience through platforms such as Wikipedia. Simultaneously, open access articles contribute to the reliability of Wikipedia as a source by affording editors timely access to novel results.

URL : Open access improves the dissemination of science: insights from Wikipedia

DOI : https://doi.org/10.1007/s11192-024-05163-4

Altmetric.com or PlumX: Does it matter?

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Authors : Behrooz Rasuli, Majid Nabavi

Facing the coronavirus disease 2019 (COVID-19) pandemic, medical publishers rose to the occasion, moving to make their full portfolio of COVID-19–related research available to read for free and expediting peer review and production processes. With such a rapid transition from paper submission to publication, however, concerns also arose regarding whether the quality of the research publication process was being affected. This article seeks to document the transformation of medical publishers’ practices in response to the COVID-19 pandemic and briefly discuss where they may go from here. For this goal, a literature search was performed in PubMed at several points to identify papers that reported early trends in how medical publishers handled COVID-19 research.

URL : Altmetric.com or PlumX: Does it matter?

DOI : https://doi.org/10.1002/leap.1625

When data sharing is an answer and when (often) it is not: Acknowledging data-driven, non-data, and data-decentered cultures

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Authors : Isto Huvila, Luanne S. Sinnamon

Contemporary research and innovation policies and advocates of data-intensive research paradigms continue to urge increased sharing of research data. Such paradigms are underpinned by a pro-data, normative data culture that has become dominant in the contemporary discourse. Earlier research on research data sharing has directed little attention to its alternatives as more than a deficit. The present study aims to provide insights into researchers’ perspectives, rationales and practices of (non-)sharing of research data in relation to their research practices.

We address two research questions, (RQ1) what underpinning patterns can be identified in researchers’ (non-)sharing of research data, and (RQ2) how are attitudes and data-sharing linked to researchers’ general practices of conducting their research. We identify and describe data-decentered culture and non-data culture as alternatives and parallels to the data-driven culture, and describe researchers de-inscriptions of how they resist and appropriate predominant notions of data in their data practices by problematizing the notion of data, asserting exceptions to the general case of data sharing, and resisting or opting out from data sharing.

URL : When data sharing is an answer and when (often) it is not: Acknowledging data-driven, non-data, and data-decentered cultures

DOI : https://doi.org/10.1002/asi.24957

Academic writing in the age of AI: Comparing the reliability of ChatGPT and Bard with Scopus and Web of Science

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Authors : Swati Garg, Asad Ahmad, Dag Øivind Madsen

ChatGPT and Bard (now known as Gemini) are becoming indispensable resources for researchers, academicians and diverse stakeholders within the academic landscape. At the same time, traditional digital tools such as scholarly databases continue to be widely used. Web of Science and Scopus are the most extensive academic databases and are generally regarded as consistently reliable scholarly research resources. With the increasing acceptance of artificial intelligence (AI) in academic writing, this study focuses on understanding the reliability of the new AI models compared to Scopus and Web of Science.

The study includes a bibliometric analysis of green, sustainable and ecological buying behaviour, covering the period from 1 January 2011 to 21 May 2023. These results are used to compare the results from the AI and the traditional scholarly databases on several parameters. Overall, the findings suggest that AI models like ChatGPT and Bard are not yet reliable for academic writing tasks. It appears to be too early to depend on AI for such tasks.

URL : Academic writing in the age of AI: Comparing the reliability of ChatGPT and Bard with Scopus and Web of Science

DOI : https://doi.org/10.1016/j.jik.2024.100563

Field-specific gold open access dynamics in the Chinese mainland: Overviews, disparities, and strategic insights

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Authors : Xinyi Chen, Zhiqiang Liu

Gold Open Access (OA) journals are crucial for scholarly communication, highlighting the need for a thorough evaluation of their academic influence on different research fields. This study leverages the InCites platform to examine article-level characteristics relating to 22 Essential Science Indicators (ESI) research fields, with a focus on the dynamics of gold OA articles, including gold OA uptake in the Chinese mainland and gold OA adoption in the domestic English-language academic journal publishing of the Chinese mainland.

The findings reveal that disparities in gold OA adoption across 22 ESI fields are more pronounced in the Chinese mainland compared with the world scenario. In the Chinese mainland, there is a significant polarization in gold OA publishing volumes across different ESI fields, particularly in Chemistry, Clinical Medicine, and Engineering.

This study builds on the understanding of OA citation advantage (OACA) by incorporating gold OA publishing volume into a two-dimensional framework, resulting in the development of a “distance” metric. It further categorizes gold OA citation effects into four quadrants: positive citation effects (quadrants A and B) and negative citation effects (quadrants C and D), based on category normalized citation impact (CNCI) and journal normalized citation impact (JNCI) indicators from the InCites database.

The findings underscore the importance of developing tailored strategies to address field-specific challenges and promote gold OA dynamics in the Chinese mainland; while prioritizing high-quality gold OA journals is essential for fostering gold OA development in the rest of the world.

URL : Field-specific gold open access dynamics in the Chinese mainland: Overviews, disparities, and strategic insights

DOI : https://doi.org/10.1002/leap.1630

FAIR GPT: A virtual consultant for research data management in ChatGPT

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Authors : Renat Shigapov, Irene Schumm

FAIR GPT is a first virtual consultant in ChatGPT designed to help researchers and organizations make their data and metadata compliant with the FAIR (Findable, Accessible, Interoperable, Reusable) principles. It provides guidance on metadata improvement, dataset organization, and repository selection.

To ensure accuracy, FAIR GPT uses external APIs to assess dataset FAIRness, retrieve controlled vocabularies, and recommend repositories, minimizing hallucination and improving precision. It also assists in creating documentation (data and software management plans, README files, and codebooks), and selecting proper licenses. This paper describes its features, applications, and limitations.

Arxiv : https://arxiv.org/abs/2410.07108

The impact of generative AI on the scholarly communications of early career researchers: An international, multi-disciplinary study

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Authors : David Nicholas, Marzena Swigon, David Clark, Abdullah Abrizah, Jorge Revez, Eti Herman, Blanca Rodríguez Bravo, Jie Xu, Anthony Watkinson

The Harbingers study of early career researchers (ECRs), their work life and scholarly communications, began by studying generational—Millennial—change (c.2016), then moved to pandemic change (c.2020) and is now investigating another potential agent of change: artificial intelligence (2024–). We report here on a substantial scoping pilot study that looks at the impact of AI on the scholarly communications of international ECRs and, extends this to the arts and humanities.

It aims to fill the knowledge gap concerning ECRs whose millennial mindset may render them especially open to change and, as the research workhorses they are, very much in the frontline. The data was collected via in-depth interviews in China, Malaysia, Poland, Portugal, Spain and (selectively) the United Kingdom/United States. The data show ECRs to be thinking, probing and, in some cases, experimenting with AI.

There was a general acceptance that AI will be responsible for the growth of low-quality scientific papers, which could lead to a decline in the quality of research. Scholarly integrity and ethics were a big concern with issues of authenticity, plagiarism, copyright and poor citation practices raised. The most widespread belief was AI would prove to be a transformative force and would exacerbate existing scholarly disparities and inequalities.

URL : The impact of generative AI on the scholarly communications of early career researchers: An international, multi-disciplinary study

DOI : https://doi.org/10.1002/leap.1628