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Purpose: Predicting highly cited papers can enable an evaluation of the potential of papers and the early detection and determination of academic achievement value. However, most highly cited paper prediction studies consider early citation information, so predicting highly cited papers by publication is challenging. Therefore, the authors propose a method for predicting early highly cited papers based on their own features. Design/methodology/approach: This research analyzed academic papers published in the Journal of the Association for Computing Machinery (ACM) from 2000 to 2013. Five types of features were extracted: paper features, journal features, author features, reference features and semantic features. Subsequently, the authors applied a deep neural network (DNN), support vector machine (SVM), decision tree (DT) and logistic regression (LGR), and they predicted highly cited papers 1–3 years after publication. Findings: Experimental results showed that early highly cited academic papers are predictable when they are first published. The authors' prediction models showed considerable performance. This study further confirmed that the features of references and authors play an important role in predicting early highly cited papers. In addition, the proportion of high-quality journal references has a more significant impact on prediction. Originality/value: Based on the available information at the time of publication, this study proposed an effective early highly cited paper prediction model. This study facilitates the early discovery and realization of the value of scientific and technological achievements. [ABSTRACT FROM AUTHOR]

Saffron is an essential medicinal plant and cash crop on this planet having significant medicinal and commercial values. The main goals of this study are to identify and analyse the scholarly articles published in the reputed Web of Science database to know the current trend in the research and conservation of saffron all over the world. The documents were selected from the 1950–2022 time period and found 3527 documents were selected in English from different authors across the globe. There are many approaches that are targeted to visualise the author impact, countries collaboration, tree map, keywords used and conservation of saffron. Since, saffron has tremendous medicinal properties and has economic values. The study is the first bibliometric investigation from the Web of Science database reporting the data published in the form of articles and representing a standard reference for visualisation of future research in the various fields of medicine, plant science, pharmacy and pharmaceuticals. [ABSTRACT FROM AUTHOR]

Bibliometrics is the application of statistical methods to analyze books, articles and other publications, especially scientific ones. Closely related to scientometrics and informetrics, to the point of overlapping and confusing. Bibliometrics refers to the study of the dynamics of the disciplines reflected in the production of their literature. It includes everything from the record of changes in the production of an academic discipline over time and between countries or regions, to the problem of the library collection. In this article some historical concepts, definitions and objectives of bibliometrics will be explained; as well as the Laws of bibliometrics; the types of analysis and bibliometric indicators most used; to finish with some examples of different types of published bibliometric studies, so that the reader can form a general idea of what he can do in this field, applying these methodologies to surgical disciplines and others as well. The aim of this manuscript was to generate a study document regarding bibliometrics as an alternative to develop research in surgery and related disciplines. [ABSTRACT FROM AUTHOR]

The International Journal of Exercise Science (IJES) publishes research from numerous subdisciplines of exercise science and health. This study documented the scholarly influence of the initial 15-year history (2008-2022) of the IJES. Publication, indexing, from the IJES website and four database services: Dimensions, Google Scholar (GS), PubMed, and SCImago Journal & Rank. The IJES has published 1055 articles in 79 issues in the first 15 years. The top 106 (10%) cited articles received a total of 7,195 citations according to GS. Top-cited IJES articles had median citations and citation rates (CR) of 48 citations and 6.5 citations/per year, respectively over a median of 8 years since their publication. Most top-cited articles were original research (68%) and reviews (9%). Top-cited articles were most often on Fitness Assessment (28%) and Technology, Epidemiology, and Physical Activity (15%) topics. In addition to its mission to support scholarly expertise of students, IJES is consistently indexed in GS with CR to top 5% cited articles similar to many journals in kinesiology/exercise science and higher than professional and highly specialized journals. The most cited articles have been in the areas of Fitness Assessment, Biomechanics and Neural Control, and Cardiovascular and Pulmonary Physiology. The IJES makes influential contributions to subsequent research in kinesiology, exercise science, and health, primarily through highly cited original research and review articles. [ABSTRACT FROM AUTHOR]

Mapping and depicting the structure, dynamics and national specialisation profiles of scientific fields at the country level affords a better understanding of national developments and changes in a given field, particularly when these changes may serve as an aid in decision-making with regard to research management. This article looks at the cognitive structure of a field over time to characterise its development across countries and to appraise the competitiveness of countries in terms of research specialisation. Based on a dataset extracted from the Scopus database, we conducted a co-word analysis and studied the degree of specialisation based on publications and on keywords, in the Nanoscience and Nanotechnology field (NST). The results reveal that NST research tends to focus on nano applications and devices. According to the keyword activity index, the countries studied centre their specialisation on electronic, biotechnology and biomedical research, certain countries showing a more competitive edge in the global realm of output. Accordingly, implications that could contribute to decision-making regarding the economy and research policies are described. [ABSTRACT FROM AUTHOR]

Metric terminologies hold immense potential for enhancing the rigor, precision, and replicability of library and information science (LIS) research. This article explores the untapped potential of metric terminologies in the realm of library and information science research. By delving into the significance of metrics, the study elucidates their role in enhancing the effectiveness and precision of scholarly communication. Investigating the diverse applications of metrics, from bibliometrics to altmetrics, the article underscores their utility in gauging research impact and shaping information dissemination strategies. Through a comprehensive examination, it unveils the myriad opportunities for leveraging metric terminologies to propel advancements in library and information science research, offering a nuanced perspective on the transformative power of metrics in the academic landscape. By embracing metric terminologies, LIS researchers can elevate the quality and impact of their contributions, propelling the field towards a more datadriven, evidence-based, and interconnected future. [ABSTRACT FROM AUTHOR]

PurposeThe present study explores and investigates the efficiency of deep learning models in identifying discourse structure and functional features and explores the potential application of natural language processing (NLP) techniques in text mining, information measurement, and scientific communication.MethodThe PLOS literature series has been utilized to obtain full-text data, and four deep learning models, including BERT, RoBERTa, SciBERT, and SsciBERT, have been employed for structure-function recognition.ResultThe experimental findings reveal that the SciBERT model performs outstandingly, surpassing the other models, with an F1 score. Additionally, the performance of different paragraph structures has been analyzed, and it has been found that the model performs well in paragraphs such as method and result.ConclusionThe study's outcomes suggest that deep learning models can recognize the structure and functional elements at the discourse level, particularly for scientific literature, where the SciBERT model performs remarkably. Moreover, the NLP techniques have extensive prospects in various fields, including text mining, information measurement, and scientific communication. By automatically parsing and identifying structural and functional information in text, the efficiency of literature management and retrieval can be improved, thereby expediting scientific research progress. Therefore, deep learning and NLP technologies hold significant value in scientific research.

The purpose of this paper is to commemorate the late scholar Loet Leydesdorff for his great academic contribution on the basis of data from Web of Science. In the span of more than 40 years, he had 526 publications, with the years 2004-2021 being the most productive (394 publications). His international collaborations spread widely across 36 countries, with Germany, the USA, the UK, China, Russia, and South Korea being the most significant. His most frequent collaboration partners included Lutz Bornmann (Germany), Staša Milojević (USA), Caroline Wagner (USA), Henry Etzkowitz (USA), Jonathan Adams (UK), Ronald Rousseau (Belgium), and Ping Zhou (China). With a broad and deep knowledge background, Leydesdorff's research extended across multiple disciplines and fields, but he was most active in library and information science and computer science. He made profound contributions to the study of bibliometrics, innovation systems (the Triple Helix model), and communications. Leydesdorff had a remarkable and extensive citation impact, with citations in 221 WoS subject categories from 120 countries. His publications in 1996, 1998, 2000, 2005, 2006, and 2012 are highly cited, and those on university-industry-government relations (the Triple Helix model) are the most cited. [ABSTRACT FROM AUTHOR]

OBJECTIVE: Intensive care units are very important across various fields of medicine, and there are many high-quality journals that publish about intensive care. However, there is a lack of information regarding which disciplines publish the most in these journals. We aim to evaluate the intensive care literature. MATERIALS AND METHODS: We searched the papers published in the American Journal of Respiratory and Critical Care Medicine, Intensive Care Medicine, Critical Care Medicine and Critical Care to gain information regarding authors’ specializations. We collected specialization data from PubMed, Google Scholar, and also from various journal websites. We examined the changes in the proportion of disciplines that are actively contributing to intensive care literature. RESULTS: Regardless of the year and the journal, intensivists were the most common writers (1,047/4,807, 21.8%) overall. This was followed by pulmonology (843, 17.5%), anesthesia (827, 17.2%), others (602, 12.5%), and pediatrics (374, 7.8%). The United States of America (1,470/30.8%), France (573/11.2%), and Germany (332/6.9%) were at the top of the list in terms of productivity. CONCLUSIONS: With the increase in the number of intensive care units and the development of an understanding of intensive care, we observed that intensivists are publishing more in intensive care literature. [ABSTRACT FROM AUTHOR]

This article analyses the evolution of the most-used terms referring to the (broad) field of bibliometrics. It compares the number of publications on bibliometrics, scientometrics, informetrics, web(o)metrics, altmetrics, and the science of science, in three international databases, the Web of Science, Scopus, and Dimensions. We found that the relative number of documents using one of the metrics-related terms is showing a more than exponential increase. This illustrates the increasing importance of metrics in the world of science. While most terms separately show a clear increase in use, web(o)metrics and perhaps, informetrics, seem to have reached their top. Bibliometrics and scientometrics are the most-used terms, with, nowadays, the term bibliometrics being used about five times more than the term scientometrics. Any comprehensive bibliometric study should make use of a combination of related keywords to cover the whole field of study. [ABSTRACT FROM AUTHOR]

Computer science is a burgeoning research field and has the potential to accelerate the rate of industrialisation and subsequently, economic development. Using bibliometric data obtained from Scopus, this study employed a 15-year informetric analysis to highlight Nigeria’s productivity and impact trends in the computer science research landscape. Our findings are summarised as follows: First, Nigeria’s computer science research contribution and citations are meager in comparison to the global output. Secondly, international collaboration is generally weak as most collaborations are national in scope. Third, Nigeria’s computer science-related research is published in low-quality outlets, as Scopus has discontinued the indexing of most of the outlets. Although, the publication growth trend is encouraging, the volume and impact of computer science-related research can improve significantly with the conduct of more quality researches that facilitated by strong international collaborations, and published in very high-quality outlets.https://dorl.net/dor/20.1001.1.20088302.2022.20.3.3.0

This “opinion article” presents the “dialogue”, namely the series of questions addressed to chatGPT and its outputs, on the question of citation index and other metrics associated with scientific publication. The AI is asked to explain basic quantities (citation index, impact factor of journals, h-index, etc) and through different questions, to give outputs on different important problems, mainly related with citation index and its biases. The AI clearly expresses that the citation index alone should not be used for evaluation purposes, and is led to predict that in certain situations a high quality scientific article would be with a low citation index. The AI also replies that the citation index depends on several factors in a complex way, and is probably not defined in an unambiguous way from a mathematical point of view, but it appears unable to explain evolutions in the field of informetrics that occurred following issues with citation index. The article concludes that the citation index is irrelevant as it is not normalized and strongly depends on the publishing journal and databases, and that it is potentially dangerous for science.

The study of topic evolution aims to analyze the behavior of different research fields by utilizing various features such as the relationships between articles. In recent years, many published papers consider more than one field of study which has led to a significant increase in the number of inter-field and interdisciplinary articles. Therefore, we can analyze the similarity/dissimilarity and convergence/divergence of research fields based on topic analysis of the published papers. Our research intends to create a methodology for studying the evolution of the research fields. In this paper, we propose an embedding approach for modeling each research topics as a multidimensional vector. Using this model, we measure the topic's distances over the years and investigate how topics evolve over time. The proposed similarity metric showed many advantages over other alternatives (such as Jaccard similarity) and it resulted in better stability and accuracy. As a case study, we applied the proposed method to subsets of computer science for experimental purposes, and the results were quite comprehensible and coherent. [ABSTRACT FROM AUTHOR]

This paper investigates the theoretical-epistemological development of altmetrics, based on the analysis of terms, expressions, definitions, and/or concepts presented in scientific literature. For this purpose, it analyzed altmetrics through a literature review, considering papers published in Portuguese, English, and Spanish, indexed in Brapci, LISA, WoS, and Scopus, since the manifesto by Priem et al. in 2010 until 2020. Given the results, it was confirmed that altmetrics is still immature and difficult to define. From the analysis of 485 papers (corpus), we found that altmetrics is named by terms and expressions that have different meanings and that its concepts and definitions are presented from three perspectives: pragmatic, genealogical, and epistemological. [ABSTRACT FROM AUTHOR]

Introduction. Given the importance of the issue of the widespread impact of scientific and technical publications in today's world, and the diversity and multiplicity of indicators for measuring these publications, it is a necessity to classify these indicators from different angles and through different tools and methods. Method. This study used documentary analysis and Delphi technique methods. The members of the Delphi panel were twenty-one experts in metric fields in information science who answered the research questionnaires several times until reaching a consensus. Analysis. Kendall’s coefficient of concordance and a one-sample t-test were used to measure the agreement of the panel members as raters on the questionnaire items. Results. A total of thirty-four sub-categories of indicators of assessment were identified which were categorised according to their similarities and differences into eight main categories as follows: measurement method, measurement unit, measurement content, measurement purpose, measurement development, measurement resource, measurability, and measurement environment. Conclusion. Classification of the indicators of evaluation for scientific and technical publications and related factors can lead to improved understanding, critique, modelling and development of indicators. The findings of this study can be considered a basis for further research and help develop evaluative theoretical foundations in scientific and technical publications and related factors.

There has been increasing interest in the study of research communities with the goal of optimizing their outcomes and impact. While current methods can predict future trends, they offer little insight about the causes of the trends. However, causal insight is important for strategic decision making to improve a community. This paper presents a new method to predict the possible causes for inefficiencies in a community by relating them to disconnections between trends, like trends in the number of publications, patents, citations, and so on. The method combines traditional scientometric and webometric metrics and metric predictions with a recent model for trend analysis in a community. The proposed method was used to analyze electronic design automation (EDA) domain. The analysis showed intriguing disconnections between the trends of the number of papers, number of granted patents, and impact of its main publications. The analysis suggests a slightly decreasing impact and visibility of EDA, while having less novel, commonly-accepted knowledge in the area. The gained insight suggests three possible strategic decisions to improve EDA community: avoiding to ignore new ideas, reducing the complexity of framed problems, and keeping a minimal gap between real-life needs and academic solutions. [ABSTRACT FROM AUTHOR]

Computer science is a burgeoning research field and has the potential to accelerate the rate of industrialization and subsequently, economic development. Using bibliometric data obtained from Scopus, this study employed a 15-year informetric analysis to highlight Nigeria's productivity and impact trends in the computer science research landscape. Our findings are summarised as follows: First, Nigeria's computer science research contribution and citations are meager in comparison to the global output. Secondly, international collaboration is generally weak as most collaborations are national in scope. Third, Nigeria's computer science-related research is published in low-quality outlets, as Scopus has discontinued the indexing of most of the outlets. Although the publication growth trend is encouraging, the volume and impact of computer science-related research can improve significantly with the conduct of more quality research facilitated by strong international collaborations, and published in very high-quality outlets. [ABSTRACT FROM AUTHOR]

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[Purpose/Significance] Analyzing the process and development achievements of the research on Humanities and Social Sciences carried out by UNESCO in recent years will help to promote China's international participation and research level, and enhance China's discourse power in the field of Humanities and Social Sciences. [Method/Process]Using the methods of informetrics and scientific knowledge graph, this paper analyzes the topic structure, hotspot areas, evolution trend and international cooperation of UNESCO research in the field of Humanities and Social Sciences from 2011 to 2020. [Results/Conclusions]The research on Humanities and Social Sciences of UNESCO has obvious interdisciplinary characteristics. Ecological environment, educational research and political ecology are its hot research fields, and sustainable development is the core topic throughout. In the international cooperation of UNESCO, European countries occupy the leading position. China should rely on its advantages, pay attention to interdisciplinary research and hot field research, promote international cooperation, and enhance its influence and voice.

BackgroundA significant public health emergency has appeared worldwide since the beginning of 2020. The spread of negative information about COVID-19 on social media poses a challenge and threat to public health disposition and the credibility of government public opinion.ObjectiveThis study aimed to analyze the rules and characteristics of government media in disseminating information on public emergencies. In addition, find ways and means to improve government media's communication power and credibility.MethodBased on relevant theories and measures of information econometrics, 10 WeChat official accounts of the Chinese government were taken as examples. The Python crawler tool was used to collect data of 10 WeChat official accounts-related tweets. In addition, this study used various tools, such as ROST, UCINET, and SPSS, for statistical analysis and co-word analysis of the data.ResultFrom January 17 to March 31, 2020, 6,612 COVID-19-related tweets were published by 10 WeChat official accounts, which broadcast epidemic overview, epidemic prevention and control, science and disinformation, epidemic assistance, epidemic impact, and negative impact. By analyzing the posting time and content of the tweets, we found that changes in the number of articles posted by the WeChat and changes in content and the progress of the COVID-19 pandemic are nearly synchronized, and most tweets are published at 8:00 am. Furthermore, based on the analytics of high dissemination index and high-frequency words, we propose that there is a significant correlation between the strength of independence and the credibility of the WeChat official account.ConclusionThe three elements of WeChat communication (value, interest, and moving) and the degree of independent innovation of public numbers impact the communication power and credibility of government media. First, if the articles published by the WeChat official account are valuable, interesting, and moving, the communication power of the WeChat official account would get more powerful. Second, increased ability for independent innovation has a positive impact on enhancing the WeChat official account's credibility. Third, government media can improve its governance effects of public health emergencies by enhancing their communication power and credibility.

This informetrics study was conducted to find out the distribution of articles and authors that published in African Journal of Library, Archives and Information Studies [AJLAIS]) from 2009 to 2018; considering the year-wise growth of research articles; authorship pattern and collaboration ratio; subject and geographical distributions of authors; and authors’ productivity level. A descriptive informetrics research design was adopted. Quota sampling technique was used to select all the articles published within the ten-year period. Data collected through a self-designed checklist was analyzed using frequency count and percentage. The findings revealed that 141 articles, contributed by 266 authors were published by AJLAIS during the period. An annual average growth of 1.20% was recorded. Overall year-wise authorship pattern revealed that majority of articles (62.41%) published in AJLAIS were multiple authored. Also, articles on Informetrics and ICT dominated the journal. Some subject areas not covered were identified such as: indexing and serial collections management. Average collaborative index across the 10-year period for the journal was 0.62. South Africa and Nigeria were the two major prolific contributors to AJLAIS, just as evidence-based research papers of survey type (65.25%) were the most common to the journal. There should be increased numbers of articles in each edition over the coming years, and awareness should be created by the publishers to familiarize the researchers with the publishing requirements of the journal. Also, LIS researchers should concentrate more on areas usually left untouched by previous studies. The study is original as no other similar study was found on publication pattern of articles in AJLAIS covering a ten year period of 2009-2018. The findings of the study will also serve as a feedback mechanism for the Publisher of the Journal and LIS researchers on how to improve the journal and LIS research in general.

Using big data has been a prevailing research trend in various academic fields. However, no studies have explored the scope and structure of big data across disciplines. In this article, we applied topic modeling and word co-occurrence analysis methods to identify key topics from more than 36,000 big data publications across all academic disciplines between 2012 and 2017. The results revealed several topics associated with the storage, collection and analysis of large datasets; the publications were predominantly published in computational fields. Other identified research topics show the influence of big data methods and techniques in areas beyond computer science, such as education, urban informatics, business, health and medical sciences. In fact, the prevalence of these topics has increased over time. In contrast, some themes like parallel computing, network modeling and big data analytic techniques have lost their popularity in recent years. These results probably reflect the maturity of big data core topics and highlight flourishing new research trends pertinent to big data in new domains, especially in social sciences, health and medicine. Findings of this article can be beneficial for researchers and science policymakers to understand the scope and structure of big data in different academic disciplines. [ABSTRACT FROM AUTHOR]

This informetrics study was conducted to find out the distribution of articles and authors that published in African Journal of Library, Archives and Information Studies [AJLAIS]) from 2009 to 2018; considering the year-wise growth of research articles; authorship pattern and collaboration ratio; subject and geographical distributions of authors; and authors' productivity level. A descriptive informetrics research design was adopted. Quota sampling technique was used to select all the articles published within the ten-year period. Data collected through a self-designed checklist was analyzed using frequency count and percentage. The findings revealed that 141 articles, contributed by 266 authors were published by AJLAIS during the period. An annual average growth of 1.20% was recorded. Overall year-wise authorship pattern revealed that majority of articles (62.41%) published in AJLAIS were multiple authored. Also, articles on Informetrics and ICT dominated the journal. Some subject areas not covered were identified such as: indexing and serial collections management. Average collaborative index across the 10-year period for the journal was 0.62. South Africa and Nigeria were the two major prolific contributors to AJLAIS, just as evidence-based research papers of survey type (65.25%) were the most common to the journal. There should be increased numbers of articles in each edition over the coming years, and awareness should be created by the publishers to familiarize the researchers with the publishing requirements of the journal. Also, LIS researchers should concentrate more on areas usually left untouched by previous studies. The study is original as no other similar study was found on publication pattern of articles in AJLAIS covering a ten year period of 2009-2018. The findings of the study will also serve as a feedback mechanism for the Publisher of the Journal and LIS researchers on how to improve the journal and LIS research in general. [ABSTRACT FROM AUTHOR]

Research data management is an umbrella term used to describe activities related to the creation, organisation, structuring, naming, backing up, storage, conservation, and sharing of research data as well as all actions that guarantee security of research data. As is often the case, researchers from Sub-Saharan Africa are lagging behind their counterparts in developed countries in embracing the best practices of research data management. One of the factors to which this slow pace of adoption of research data management could be attributed, is inadequate research on the subject. The purpose of this paper is to analyse the quantity, quality, visibility and authorship of publications on research data management in Sub-Saharan Africa. Bibliometrics approaches were used to analyse publications on research data management from, and on, Sub-Saharan Africa which are currently indexed in Google Scholar. The index was chosen because it is free and is reputed to have liberal selection criteria which do not favour, or discriminate, any discipline or geographic regions. Data was retrieved from Google Scholar using Harzing’s “Publish or Perish” software and analysed using VOSviewer. The findings of the study revealed that the quantity, quality, visibility and authorship collaboration of scholarly publications on research data management in Sub-Saharan Africa is low. The findings may be used by libraries and research institutions in Sub-Saharan Africa to develop and promote best practices in research data management as a means of enhancing their research output and impact.

Information literacy skills are requisite to fulfilling one's potential and are highly connected to a good quality of life. However, the ways in which information literacy is discussed within the academic canon are largely unexplored, particularly as these conversations take place through different cultural lenses. The ways in which such cultures are grouped often rely on traditional methods of geographic clustering that are increasingly complicated by the disparate internal nature of societies. Using text analysis of a large bibliometric data set, this research is an attempt to examine how scholars around the world discuss information literacy in their publications. The authors pulled 3658 records with the exact term "information literacy" from the Scopus database. This data was analyzed for the most frequently employed words and phrases, and grouped by country. The authors then further grouped the countries by their levels of literacy, Human Development Index ranking, the average number of citations per article, and a metric created by the authors that assessed each country's progress in regard to the Sustainable Development Goals and population health. The results include a discussion of the differences in the ways that scholars from different cultures discuss information literacy, and a number of data visualizations to highlight differences in the data. [ABSTRACT FROM AUTHOR]

Dividing papers based on their numbers of citations into several groups constitutes one of the most common research practices in bibliometrics and beyond. However, existing dividing methods are both arbitrary and subject to bias. This article proposes a novel approach to partition highly, medium and lowly cited publications based on their citation distribution. We utilise the whole Web of Science (WoS) dataset to demonstrate how to apply this approach to scholarly datasets and examine the robustness of our algorithm in each of the six disciplines under the WoS dataset. The codes that underlie the algorithm are available online. [ABSTRACT FROM AUTHOR]

Research excellence (RE) is a relatively new concept which has been gaining traction among scholars, government agencies and funders. No universally accepted definition of RE exists. In this paper, however, it is perceived as the sustained conceptualisation, design, execution and dissemination of optimal volumes of high quality research products which contribute effectively to societal wellbeing. The concept of research excellence is just emerging in Kenya. Indeed, the literature reviewed in this paper reveals that the perception, measurement, and reporting of research excellence in Kenya is largely unknown. Therefore, this paper seeks to unravel these issues as a means of promoting research excellence in the country. The study anchoring this paper assessed the top papers produced in Kenya to gauge the country's RE. Data were obtained from Clarivate Analytics' Web of Science (WoS) Core Collection databases, the Essential Science Indicators and the Journal Citation Reports. Specifically, the paper explores the trend and volume of the highly cited and hot papers as the percentage share of Kenya's total research publications; identifies the journals and assessed the quality of the journals in which Kenya's highly cited and hot papers are published; examines the subject content and research field yielding the most highly cited and hot research papers in Kenya; determines the extent of research collaboration in the highly cited and hot papers; and benchmarks Kenya's performance in the top papers against the rest of Africa. The study reveals an increase in the publication of the top papers, largely in the form of journal articles; a heavy co-authorship of the papers; a favourable performance by Kenya when compared to the rest of the African countries; and the publication of the country's top papers in prestigious international journals. Kenya's RE is partly dependent on the dissemination of its research in high impact factor journals. In addition, the country's RE is heavily dependent on the performance of science fields such as internal medicine, environmental sciences and ecology, and public health and agriculture. [ABSTRACT FROM AUTHOR]

Background: Publication activity in the field of anesthesiology informs decisions that enhance academic advancement. Most previous bibliometric studies on anesthesiology examined data limited to journals focused on anesthesiology rather than data answerable to authors in anesthesia departments. This study comprehensively explored publication trends in the field of anesthesiology and their impact. We hypothesized that anesthesiology's bibliometric scene would differ based on whether articles in the same study period were published in anesthesiology-focused journals or were produced by authors in anesthesia departments but published in non-specialty journals.Methods: This cross-sectional study used bibliometric data from the Science Citation Index Expanded database between 1999 and 2018. Two datasets were assembled. The first dataset was a subject-dataset (articles published in 31 journals in the anesthesiology category of InCites Journal Citation Reports in 2018); the second dataset was the department-dataset (articles published in the Science Citation Index Expanded by authors in anesthesia departments). We captured the bibliographical record of each article in both datasets and noted each article's Institute for Scientific Information code, publication year, title, abstract, author addresses, subject category, and references for further study.Results: A total of 69,593 articles were published—cited 1,497,932 times—in the subject-dataset; a total of 167,501 articles were published—cited 3,731,540 times—in the department-dataset. The results demonstrate differences between the two datasets. First, the number of articles was stagnant, with little growth (average annual growth rate = 0.31%) in the subject-dataset; whereas there was stable growth (average annual growth rate = 4.50%) in articles in the department-dataset. Second, only 30.4% of anesthesia department articles were published in anesthesiology journals. Third, journals related to “pain” had the lowest department-subject ratio, which was attributable to a large portion of non-anesthesia department researchers' participation in related research.Conclusions: This study showed that articles published in anesthesiology-focused and non-specialty journals demonstrate fundamentally different trends. Thus, it not only helps researchers develop a more comprehensive understanding of the current publication status and trends in anesthesiology, but also provides a basis for national academic organizations to frame relevant anesthesiology development policies and rationalize resource allocation.

This article surveys topic distributions of the academic literature that employs the terms bibliometrics, scientometrics, and informetrics. This exploration allows informing on the adoption of those terms and publication patterns of the authors acknowledging their work to be part of bibliometric research. We retrieved 20,268 articles related to bibliometrics and applied methodologies that exploit various features of the dataset to surface different topic representations. Across them, we observe major trends including discussions on theory, regional publication patterns, databases, and tools. There is a great increase in the application of bibliometrics as science mapping and decision-making tools in management, public health, sustainability, and medical fields. It is also observed that the term bibliometrics has reached an overall generality, while the terms scientometrics and informetrics may be more accurate in representing the core of bibliometric research as understood by the information and library science field. This article contributes by providing multiple snapshots of a field that has grown too quickly beyond the confines of library science.

Scientific software is a fundamental player in modern science, participating in all stages of scientific knowledge production. Software occasionally supports the development of trivial tasks, while at other instances it determines procedures, methods, protocols, results, or conclusions related with the scientific work. The growing relevance of scientific software as a research product with value of its own has triggered the development of quantitative science studies of scientific software. The main objective of this study is to illustrate a link-based webometric approach to characterize the online mentions to scientific software across different analytical frameworks. To do this, the bibliometric software VOSviewer is used as a case study. Considering VOSviewer's official website as a baseline, online mentions to this website were counted in three different analytical frameworks: academic literature via Google Scholar (988 mentioning publications), webpages via Majestic (1,330 mentioning websites), and tweets via Twitter (267 mentioning tweets). Google scholar mentions shows how VOSviewer is used as a research resource, whilst mentions in webpages and tweets show the interest on VOSviewer's website from an informational and a conversational point of view. Results evidence that URL mentions can be used to gather all sorts of online impacts related to non-traditional research objects, like software, thus expanding the analytical scientometric toolset by incorporating a novel digital dimension. [ABSTRACT FROM AUTHOR]

The rise of "cloud-computing, mobile-Internet, Internet of things, big-data, and smart-data" digital technology has brought a subversive revolution to enterprises and consumers' traditional patterns. Product research and development has become the main battlefield of enterprise competition, facing an environment where challenges and opportunities coexist. Regarding the concepts and methods of product R&D projects, the domestic start was later than the international ones, and many domestic companies have also used successful foreign cases as benchmarks to innovate their management methods in practice. "Workers must first sharpen their tools if they want to do their jobs well". This article will start from the relevant concepts of product R&D projects and summarize current R&D management ideas and methods. We combined the bibliometric analysis software Histcite and Citespace to sort out the content of domestic and foreign literature and explore the changing trends of research hotspots. Finally, combined with the analysis of confirmed cases in domestic masters and doctoral dissertations to test the theory, the literature review of the product R&D project management theme was carried out from the dual perspectives of comprehensive theory and practice. This study uses the core collection library of Web of Science as the object of document extraction. Based on the search conditions of "Product development" or "Intergrat* product development", 8998 sample documents were initially retrieved. The search deadline was June 2019, with a time range from 2000 to June 2019. Then, using the record number of 50 as the critical condition, 5007 analysis samples were deleted, refined, and cleaned. Through the review and measurement of 5007 papers, the analysis showed that: (1) in the last ten years, sustainability, consumer focus, new approaches to product development management, and organizational design have become critical considerations in the product development process stage; (2) at this stage, researchers are paying more attention to the innovation, design, product development, identification, simultaneous engineering, consequence, and stage/gate model aspects of product development; and (3) factors such as long development cycles, high costs, and poor organizational design are now common problems in the product development process. [ABSTRACT FROM AUTHOR]

Research data management (RDM) is the all-encompassing term used to describe the processes and activities related to the creation, storage, security, preservation, retrieval, reuse and sharing of research data. As is often the case, researchers from Sub-Saharan Africa are lagging behind their counterparts in developed countries in embracing best practices in research data management. One of the factors to which this slow pace of adoption of research data management could be attributed, is inadequate research on the subject. This paper analyses the authorship, volume, visibility and quality of publications on research data management in Sub-Saharan Africa. The analysis was done using bibliometrics. The units of analysis were publications on research data management from, and on, Sub-Saharan Africa which are currently indexed in Google Scholar. This index was chosen because it is free and is reputed for its liberal selection criteria which does not favour, or discriminate, any discipline or geographic region. Data from Google Scholar was retrieved using Harzing's "Publish or Perish" software and analysed using Nees Jan van Eck's VOSviewer software. The findings of the study revealed that authorship collaboration, visibility, quality, and quantity of scholarly publications on research data management in Sub-Saharan Africa is low when compared to developed countries like the United States of America, the United Kingdom, Canada and Australia. [ABSTRACT FROM AUTHOR]

Innovations in dental sciences are potentially disruptive; however, the language barrier in the case of Latin America and the Caribbean (LAC) limits access to scientific studies. There is a necessity to measure the development of dental research across the LAC region, where economic power and postgraduate education access vary significantly. This article aims to analyze documents, citations, and journals and compare the SJR, H-Index, citation rates, and Co-occurrence Networks (Keywords) between dental journals published in LAC and the rest of the world, according to the report of Scimago Journal and Country Rank, between the years 1996 and 2020. Results show that Brazil leads dental research in the LAC, scoring the highest number of published documents, citations, and SJR metrics. The mean H-index and SJR of LAC dentistry journals are significantly lower than those of other regions (p < 0.03); however, there are no significant differences in the mean total citations in the last 3 years between LAC and other regions (p > 0.15). This suggests that the articles published in dentistry journals from LAC are being cited in similar proportions to the journals of other regions, but a large portion of these citations came from publications with low scientific impact.