Artificial Intelligence (AI) is a rapidly developing field of research that attracts significant funding from both the state and industry players. Such interest is driven by a wide range of AI... Show moreArtificial Intelligence (AI) is a rapidly developing field of research that attracts significant funding from both the state and industry players. Such interest is driven by a wide range of AI technology applications in many fields. Since many AI research topics relate to computer science, where a significant share of research results are published in conference proceedings, the same applies to AI. The world leaders in artificial intelligence research are China and the United States. The authors conducted a comparative analysis of the bibliometric indicators of AI conference papers from these two countries based on Scopus data. The analysis aimed to identify conferences that receive above-average citation rates and suggest publication strategies for authors from these countries to participate in conferences that are likely to provide better dissemination of their research results. The results showed that, although Chinese researchers publish more AI papers than those from the United States, US conference papers are cited more frequently. The authors also conducted a correlation analysis of the MNCS index, which revealed no high correlation between MNCS USA vs. MNCS China, MNCS China/MNCS USA vs. MSAR, and MNCS China/MNCS USA vs. CORE ranking indicators. Show less
This dissertation offers an in-depth evaluation of the Brazilian National System of Graduate Education (SNPG), overseen by the Brazilian Agency for Support and Evaluation of Graduate Education ... Show moreThis dissertation offers an in-depth evaluation of the Brazilian National System of Graduate Education (SNPG), overseen by the Brazilian Agency for Support and Evaluation of Graduate Education (CAPES). Anchored at the crossroads of research evaluation, scientometrics, and science policy, the study employs a multi-faceted methodology to dissect the complex dynamics between evaluation mechanisms, academic productivity, societal influence, and policy repercussions in Brazil.Organised into four parts, the study opens by tracing the historical evolution of graduate education and its evaluative mechanisms in Brazil. The following section introduces an international perspective to the country's research system and its evaluation, including a comparative analysis with the evaluation model practiced in The Netherlands. The third part adopts a mixed-methods analysis to examine fundamental evaluative instruments in the Brazilian context, notably those pertaining to scholarly publication metrics. The final part confronts the challenges precipitated by the SNPG's rapid expansion and advocates for self-assessment approaches as a means to integrate a more multi-dimensional evaluation framework.In its conclusion, the research cautions that Brazil's performance-oriented evaluation model, while fostering scientific development, may inadvertently stifle innovation and diversity. The author argues in favor of revising existing paradigms to adopt a more context-sensitive and holistic evaluative approach. Show less
Sandler, D.G.; Gladyrev, D.A.; Kochetkov, D.; Zorina, A.D. 2022
Relevance. One of the main goals of state university support programs in Russia is to increase the number of scientific publications. In 2021, Project 5-100 was replaced by the program PRIORITY... Show moreRelevance. One of the main goals of state university support programs in Russia is to increase the number of scientific publications. In 2021, Project 5-100 was replaced by the program PRIORITY 2030 (Strategic Academic Leadership Program). The new program increased the significance of the factors affecting the number of publications in universities and the issue of the optimal allocation of funding among research groups.Research objective. This study examines the factors that affect the productivity of research groups at the university. Unlike the majority of other studies on this topic, this study analyzes scientific productivity at the level of research groups.Data and methods. The study was possible due to the availability of data for 79 research groups at the Ural Federal University for the period from 2014 to 2020. The total number of articles and the number of articles in journals with an impact factor of more than two were used as indicators of research groups’ performance. To determine the factors influencing these indicators, we used econometric models for panel data. We used two separate samples: for social sciences and humanities and for other sciences.Results. We identified the following factors affecting the performance of research groups: the number of participants, the age of the research group, the supervisor’s scientific age, and the amount of funding (the possibility of obtaining more funds or being denied funds). The most interesting result is the following: the supervisor's scientific age and increased funding have a negative impact on the group’s performance. The article provides possible explanations for these results.Conclusion. Since the purpose of creating and funding research groups is primarily to increase their productivity, the results may be in favor of younger supervisors. University managers may also be interested in the ambiguous impact of increased funding: we suppose that research groups are more motivated not by the actual funding but by the prospective amount they may get. Show less
As the COVID-19 pandemic unfolds, researchers from all disciplines are coming together and contributing their expertise. CORD-19, a dataset of COVID-19 and coronavirus publications, has been made... Show moreAs the COVID-19 pandemic unfolds, researchers from all disciplines are coming together and contributing their expertise. CORD-19, a dataset of COVID-19 and coronavirus publications, has been made available alongside calls to help mine the information it contains and to create tools to search it more effectively. We analyse the delineation of the publications included in CORD-19 from a scientometric perspective. Based on a comparison to the Web of Science database, we find that CORD-19 provides an almost complete coverage of research on COVID-19 and coronaviruses. CORD-19 contains not only research that deals directly with COVID-19 and coronaviruses, but also research on viruses in general. Publications from CORD-19 focus mostly on a few well-defined research areas, in particular: coronaviruses (primarily SARS-CoV, MERS-CoV and SARS-CoV-2); public health and viral epidemics; molecular biology of viruses; influenza and other families of viruses; immunology and antivirals; clinical medicine. CORD-19 publications that appeared in 2020, especially editorials and letters, are disproportionately popular on social media. While we fully endorse the CORD-19 initiative, it is important to be aware that CORD-19 extends beyond research on COVID-19 and coronaviruses. Show less
The cognitive and social structures, and publication practices, of the humanities have been studied bibliometrically for the past 50 years. This article explores the conceptual frameworks, methods,... Show moreThe cognitive and social structures, and publication practices, of the humanities have been studied bibliometrically for the past 50 years. This article explores the conceptual frameworks, methods, and data sources used in bibliometrics to study the nature of the humanities, and its differences and similarities in comparison with other scientific domains. We give a historical overview of bibliometric scholarship between 1965 and 2018 that studies the humanities empirically and distinguishes between two periods in which the configuration of the bibliometric system differs remarkably. The first period, 1965 to the 1980s, is characterized by bibliometric methods embedded in a sociological theoretical framework, the development and use of the Price Index, and small samples of journal publications from which references are used as data sources. The second period, the 1980s to the present day, is characterized by a new intellectual hinterland-that of science policy and research evaluation-in which bibliometric methods become embedded. Here metadata of publications becomes the primary data source with which publication profiles of humanistic scholarly communities are analyzed. We unpack the differences between these two periods and critically discuss the analytical avenues that different approaches offer. Show less
To what extent is scientific research related to societal needs? To answer this crucial question systematically we need to contrast indicators of research priorities with indicators of societal... Show moreTo what extent is scientific research related to societal needs? To answer this crucial question systematically we need to contrast indicators of research priorities with indicators of societal needs. We focus on rice research and technology between 1983 and 2012. We combine quantitative methods that allow investigation of the relation between ‘revealed’ research priorities and ‘revealed’ societal demands, measured respectively by research output (publications) and national accounts of rice use and farmers’ and consumers’ rice-related needs. We employ new bibliometric data, methods and indicators to identify countries’ main rice research topics (priorities) from publications. For a panel of countries, we estimate the relation between revealed research priorities and revealed demands. We find that, across countries and time, societal demands explain a country's research trajectory to a limited extent. Some research priorities are nicely aligned to societal demands, confirming that science is partly related to societal needs. However, we find a relevant number of misalignments between the focus of rice research and revealed demands, crucially related to human consumption and nutrition. We discuss some implications for research policy. Show less
Mahieu, R.; Eck, N.J.P. van; Van Putten, D.; Van den Hoven, J. 2018
Our lives are increasingly intertwined with the digital realm, and with new technology, new ethical problems emerge. The academic field that addresses these problems—which we tentatively call ... Show moreOur lives are increasingly intertwined with the digital realm, and with new technology, new ethical problems emerge. The academic field that addresses these problems—which we tentatively call ‘digital ethics’—can be an important intellectual resource for policy making and regulation. This is why it is important to understand how the new ethical challenges of a digital society are being met by academic research. We have undertaken a scientometric analysis to arrive at a better understanding of the nature, scope and dynamics of the field of digital ethics. Our approach in this paper shows how the field of digital ethics is distributed over various academic disciplines. By first having experts select a collection of keywords central to digital ethics, we have generated a dataset of articles discussing these issues. This approach allows us to generate a scientometric visualisation of the field of digital ethics, without being constrained by any preconceived definitions of academic disciplines. We have first of all found that the number of publications pertaining to digital ethics is exponentially increasing. We furthermore established that whereas one may expect digital ethics to be a species of ethics, we in fact found that the various questions pertaining to digital ethics are predominantly being discussed in computer science, law and biomedical science. It is in these fields, more than in the independent field of ethics, that ethical discourse is being developed around concrete and often technical issues. Moreover, it appears that some important ethical values are very prominent in one field (e.g., autonomy in medical science), while being almost absent in others. We conclude that to get a thorough understanding of, and grip on, all the hard ethical questions of a digital society, ethicists, policy makers and legal scholars will need to familiarize themselves with the concrete and practical work that is being done across a range of different scientific fields to deal with these questions. Show less
Costas, R.; Perianes-Rodriguez, A.; Ruiz-Castillo, J. 2017
PurposeThe introduction of “altmetrics” as new tools to analyze scientific impact within the reward system of science has challenged the hegemony of citations as the predominant source for... Show morePurposeThe introduction of “altmetrics” as new tools to analyze scientific impact within the reward system of science has challenged the hegemony of citations as the predominant source for measuring scientific impact. Mendeley readership has been identified as one of the most important altmetric sources, with several features that are similar to citations. The purpose of this paper is to perform an in-depth analysis of the differences and similarities between the distributions of Mendeley readership and citations across fields.Design/methodology/approachThe authors analyze two issues by using in each case a common analytical framework for both metrics: the shape of the distributions of readership and citations, and the field normalization problem generated by differences in citation and readership practices across fields. In the first issue the authors use the characteristic scores and scales method, and in the second the measurement framework introduced in Crespo et al. (2013).FindingsThere are three main results. First, the citations and Mendeley readership distributions exhibit a strikingly similar degree of skewness in all fields. Second, the results on “exchange rates (ERs)” for Mendeley readership empirically supports the possibility of comparing readership counts across fields, as well as the field normalization of readership distributions using ERs as normalization factors. Third, field normalization using field mean readerships as normalization factors leads to comparably good results.Originality/valueThese findings open up challenging new questions, particularly regarding the possibility of obtaining conflicting results from field normalized citation and Mendeley readership indicators; this suggests the need for better determining the role of the two metrics in capturing scientific recognition. Show less
