Search

This study aimed to identify and analyze the characteristics of highly cited publications in the field of artificial intelligence within the Science Citation Index Expanded from 1991 to 2022. The assessment focused on documents that garnered 100 citations or more from the Web of Science Core Collection, spanning from their publication date to the end of 2022. Various aspects of these documents were analyzed, encompassing document types, the distribution of annual production, the average number of citations per publication, Web of Science categories, and journals. Moreover, the publication performance of countries, institutions, and authors underwent evaluation through six publication indicators and associated citation metrics. To facilitate a comprehensive comparison of the authors research performance, the Y-index was employed. The outcomes of the analysis revealed that a majority of the highly cited articles were published within the Web of Science categories of "artificial intelligence computer science" and "electrical and electronic engineering". Notably, the United States exhibited dominance across all six publication indicators. Within the realm of average citations per publication, the United Kingdom emerged as a leader for independent articles, first-author articles, and corresponding-author articles. Exceptionally, the Chinese Academy of Sciences in China and the Massachusetts Institute of Technology (MIT) in the USA, contributed significantly. The significant impact of highly cited articles extended to the output of Stanford University in the USA. B.L. Bassler published the most highly cited articles. Upon employing the Y-index analysis, J.E.P. Santos was identified as having the highest potential for publication. In addition to the primary analysis, this study also presented nine classic articles that have left an indelible mark on artificial intelligence research.

The current situation of open research data in Spanish university repositories is analyzed by means of twelve indicators that allow us to compare them with each other. The twelve self-developed indicators deal with research datasets and institutional policies linked to open access, as well as some of the key characteristics of the repositories. The methodology used consists of comparing the repositories of the different universities linked to REBIUN. The result has been that datasets in institutional repositories are scarce, and the situation is heterogeneous across the territory. This raises questions about future open access policies for research data in the country's main scientific institutions., Comment: 17 pages, 9 Figures

Artificial intelligence (AI) is gradually changing the planet. Data digitisation, computing infrastructure and machine learning are helping AI tools to spread across all sectors of society. This article presents the results of a bibliometric analysis of AI-related publications in the social sciences over the last ten years (2013-2022). Most of the historical publications are taken into consideration with the aim of identifying research relevance and trends in this field. The results indicate that more than 19,408 articles have been published, 85% from 2008 to 2022, showing that research in this field is increasing significantly year on year. Clear domains or disciplines of research related to AI within the social sciences can be grouped into sub-areas such as law and legal reasoning, education, economics, and ethics. The United States is the country that publishes the most (20%), followed by China (13%). The influence of AI on society is inevitable and the advances can generate great opportunities for innovation and new jobs, but in the medium term it is necessary to adequately face this transition, setting regulations and reviewing the challenges of ethics and responsibility.

Despite the advance of the Open Access (OA) movement, most scholarly production can only be accessed through a paywall. We conduct an international survey among researchers (N=3,304) to measure the willingness and motivations to use (or not use) scholarly piracy sites, and other alternatives to overcome a paywall such as paying with their own money, institutional loans, just reading the abstract, asking the corresponding author for a copy of the document, asking a colleague to get the document for them, or searching for an OA version of the paper. We also explore differences in terms of age, professional position, country income level, discipline, and commitment to OA. The results show that researchers most frequently look for OA versions of the documents. However, more than 50% of the participants have used a scholarly piracy site at least once. This is less common in high-income countries, and among older and better-established scholars. Regarding disciplines, such services were less used in Life & Health Sciences and Social Sciences. Those who have never used a pirate library highlighted ethical and legal objections or pointed out that they were not aware of the existence of such libraries.

The rise of open access (OA) publishing has been followed by the expansion of the Article Publishing Charges (APC) that moves the financial burden of scholarly journal publishing from readers to authors. We introduce the results of an international randomly selected sampled survey (N=3,422) that explores attitudes towards this pay-to-publish or Gold OA model among scholars. We test the predictor role of age, professional position, discipline, and income-level country in this regard. We found that APCs are perceived more as a global threat to Science than a deterrent to personal professional careers. Academics in low and lower-middle income level countries hold the most unfavorable opinions about the APC system. The less experimental disciplines held more negative perceptions of APC compared to STEM and the Life Sciences. Age and access to external funding stood as negative predictors of refusal to pay to publish. Commitment to OA self-archiving predicted the negative global perception of the APC. We conclude that access to external research funds influences the acceptance and the particular perception of the pay to publish model, remarking the economic dimension of the problem and warning about issues in the inequality between center and periphery.

This paper presents an analysis of the publication of datasets collected via Google Dataset Search, specialized in families of RNA viruses, whose terminology was obtained from the National Cancer Institute (NCI) thesaurus developed by the US Department of Health and Human Services. The objective is to determine the scope and reuse capacity of the available data, determine the number of datasets and their free access, the proportion in reusable download formats, the main providers, their publication chronology, and to verify their scientific provenance. On the other hand, we also define possible relationships between the publication of datasets and the main pandemics that have occurred during the last 10 years. The results obtained highlight that only 52% of the datasets are related to scientific research, while an even smaller fraction (15%) are reusable. There is also an upward trend in the publication of datasets, especially related to the impact of the main epidemics, as clearly confirmed for the Ebola virus, Zika, SARS-CoV, H1N1, H1N5, and especially the SARS-CoV-2 coronavirus. Finally, it is observed that the search engine has not yet implemented adequate methods for filtering and monitoring the datasets. These results reveal some of the difficulties facing open science in the dataset field.

This paper aims to gain a better understanding of the perspectives of contributors to Spanish academic journals regarding open access, open peer review, and altmetrics. It also explores how age, gender, professional experience, career history, and perception and use of social media influence authors opinions toward these developments in scholarly publishing. A sample of contributors (n-1254) to Spanish academic journals was invited to participate in a survey about the aforementioned topics. The response rate was 24 per cent (n-295). Contributors to Spanish scholarly journals hold a favourable opinion of open access but were more cautious about open peer review and altmetrics. Younger and female scholars were more reluctant to accept open peer review practices. A positive attitude toward social networks did not necessarily translate into enthusiasm for emerging trends in scholarly publishing. Despite this, ResearchGate users were more aware of altmetrics.

This paper presents a thorough bibliometric analysis of research published in Annals of Library and Information Studies (ALIS), an India-based journal, for the period 2011_2017. Specifically, it compares this journal's trends with those of other library and information science (LIS) journals from the same geographical area (India, and Asia as a whole) and with the 10 highest-rated LIS journals worldwide. The source of the data used was the multidisciplinary database Scopus. To perform this comparison, ALIS' production was analyzed in order to identify authorship patterns; for example, authors' countries of residence, co-authorship trends, and collaboration networks. Research topics were identified through keyword analysis, while performance was measured by examining the number of citations articles received. This study provides substantial information. The research lines detected through examining the keywords in ALIS articles were determined to be similar to those for the top LIS journals in both Asia and worldwide. Specifically, ALIS authors are focusing on metrics, bibliometrics, and social networking, which follows global trends. Notably, however, collaboration among Asia-based journals was found to be lower than that in the top-indexed journals in the LIS field. The results obtained present a roadmap for expanding the research in this field., Comment: 7 Tables, 3 Figures, 16 pages