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Se analiza la productividad de los autores que publicaron artículos en la revista Contratexto, desde 1985 hasta 2022, se busca identificar a los autores más productivos y aquellos que constituyen el núcleo de autores productores. Para ello, se construyó una base de datos bibliográfica dedicada a la revista en el gestor de referencias Endnote X9; posteriormente, los datos fueron exportados a Excel y trabajados con los paquetes nls2 y proto del Proyecto R. La productividad de los autores fue medida con la Ley de Lotka mediante el modelo del poder inverso generalizado, en el análisis de los datos se consideraron las tres formas de conteo: directo, completo y fraccionado. Para medir el ajuste de los datos observados a la distribución de Lotka para cada una de las formas de conteo se usaron la prueba chi-cuadrado y Kolmogorov-Smirnov. Se encontró que el modelo del poder inverso generalizado para las tres formas de conteo se ajusta a la distribución de Lotka. Se encontró también una alta concentración de autores con un solo artículo publicado en la revista en sus 38 años de existencia, los autores más productivos en el periodo de estudio en su mayoría están vinculados a la universidad que edita la revista = The productivity of the authors who published articles in the journal Contratexto, from 1985 to 2022, was analyzed to identify the most productive authors and those who constitute the core of producing authors. For this purpose, a bibliographic database dedicated to the journal was built in the Endnote X9 reference manager; subsequently, the data were exported to Excel and processed in Project R. The productivity of the authors was measured with Lotka’s Law using the generalized inverse power model; the three forms of counting were considered in the analysis of the data: direct, complete, and fractional. The chi-square test and Kolmogorov-Smirnov test were used to measure the fit of the observed data to the Lotka distribution for each of the counting methods. The generalized inverse power model for the three counting forms was found to fit Lotka’s distribution. A high concentration of authors with only one article published in the journal in its 38 years of existence was also found; the most productive authors in the studied period are mostly linked to the university that publishes the journal.

The productivity of the authors who published articles in the journal Contratexto, from 1985 to 2022, was analyzed to identify the most productive authors and those who constitute the core of producing authors. For this purpose, a bibliographic database dedicated to the journal was built in the Endnote X9 reference manager; subsequently, the data were exported to Excel and processed in Project R. The productivity of the authors was measured with Lotka's Law using the generalized inverse power model; the three forms of counting were considered in the analysis of the data: direct, complete, and fractional. The chi-square test and Kolmogorov-Smirnov test were used to measure the fit of the observed data to the Lotka distribution for each of the counting methods. The generalized inverse power model for the three counting forms was found to fit Lotka's distribution. A high concentration of authors with only one article published in the journal in its 38 years of existence was also found; the most productive authors in the studied period are mostly linked to the university that publishes the journal. [ABSTRACT FROM AUTHOR]

Literary warrants on 'Digital Citizenship' published since its inception are still countable. The search executed to identify the bibliometric literature on ‘Digital Citizenship’ retrieved a meager outcome. Therefore, the study was pivoted with the data retrieved from the SCOPUS database. By utilizing normalized data and citation analysis to evaluate the influence across the various groupings, it is possible to see an almost linear rise in 2021 on the topic. Statistical and visual modeling software tools (R-Biblioshiny, Bibliometrix) were used in the study. It examines what this means for how bibliometric methodologies are used and disseminated in various situations. The study by the authors addressed bibliometric analysis and categorization of articles as per Ribble and Choi. Moreover, the paper discussed three field Plots (Sources-Keywords-Authors) and the most relevant authors. Furthermore, the study tried to testify to the fitness of Bradford's Law, trending topics on the subject, co-occurrence network by keywords, topic growth over the year, and a thematic map of topics from 1999 to 2022. The results were quite impressive. out of a total of 377 articles on digital citizenship, a scattering of subjects with numerous overlapped concepts like digital literacy, digital competence, higher education, technology, digital divide, cyber-bullying, information literacy, digital citizenship education, privacy, secondary education, adolescents, digital education, empowerment, primary education, university students have been identified.

The Present study focuses on authorship patterns in Knowledge Management using scientometrics. The study found Del Giudice M as the most productive author with an h-Index of 20. The study found that Del Giudice M. is the most locally cited author with 25 articles with a fractionalised value of 7.05. The study identified Del Giudice M, Lee S, Bontis N, Ferraris A, and Serenko A as the most prolific authors from 2010 to 2023 The most striking observation is the presence of an Indian author, whose paper published in the Journal of Service Research was cited 738 times with a TCpY of 52.71. The study also reveals that more documents were collaborative, which accounts for the prevalence of publications with multiple authors with the USA leading the scene. This study deliberates mostly on authorship patterns in Scientometric research connected to Knowledge Management to cultivate a fairer, more varied, and influential research environment that accurately represents the depth and complexity of Knowledge Management practices and issues. This paper analysis Lotka’s Law, Most Local Cited Authors in KM, the authorship pattern, most locally cited authors, the productivity of authors over time, and most globally cited publications in Knowledge Management. [ABSTRACT FROM AUTHOR]

This paper deals with a new stochastic method to solve Lotka's Law with higher degree of Newton-Cotes Quadrature Rule as an alternate method to existing solution of the value determination of the constant part of the power law; so far, M.L. Pao gave a solution with an equation to determine the area under the curve with numerical integration rule with degree=1 which is also known as Trapezoidal Rule. Here, next higher degree 2, popularly known as Simpson's 1/3 rule at closed interval [x 1,] has been used to establish a deterministic equation form to solve authors' productivity realized through Lotka's Law. Re-estimating the value of C with higher degree quadrature rule is very crucial as the probability of inclusion of more area and exclusion of unnecessary area under the curve is more precise. Another area of investigation is the determination of p value (Pao determined p=20), i.e. whether p=20 can be altered? Or equation derived through Simpson's 1/3 rule, whether it can give a minimal residual error beyond p=20. This paper is dedicated to build up a mathematical equation to solve the constant value(C) of the Lotka's law equation as well as enlighten all these investigating points. [ABSTRACT FROM AUTHOR]

Literary warrants on 'Digital Citizenship' published since its inception are still countable. The search executed to identify the bibliometric literature on 'Digital Citizenship' retrieved a meager outcome. Therefore, the study was pivoted with the data retrieved from the SCOPUS database. By utilizing normalized data and citation analysis to evaluate the influence across the various groupings, it is possible to see an almost linear rise in 2021 on the topic. Statistical and visual modeling software tools (R-Biblioshiny, Bibliometrix) were used in the study. It examines what this means for how bibliometric methodologies are used and disseminated in various situations. The study by the authors addressed bibliometric analysis and categorization of articles as per Ribble and Choi. Moreover, the paper discussed three field Plots (Sources-Keywords-Authors) and the most relevant authors. Furthermore, the study tried to testify to the fitness of Bradford's Law, trending topics on the subject, co-occurrence network by keywords, topic growth over the year, and a thematic map of topics from 1999 to 2022. The results were quite impressive. out of a total of 377 articles on digital citizenship, a scattering of subjects with numerous overlapped concepts like digital literacy, digital competence, higher education, technology, digital divide, cyber-bullying, information literacy, digital citizenship education, privacy, secondary education, adolescents, digital education, empowerment, primary education, university students have been identified. [ABSTRACT FROM AUTHOR]

Introduction. The purpose of this study is to use Lotka's law to determine the pattern of author output in the field of Library Science in the Library Science Journal Q1 indexed by Scopus. Data Collection Methods. The quantitative descriptive method was conducted, with a bibliometric approach to explore aspects of scientific articles. Data Analysis. The research data was acquired from the Scopus International Journal, which can be viewed at www.scopus.com from 2018 to 2022, with article types. Results and Discussion. The research results found that the number of library science journals indexed by Scopus Q1 was 61. Based on the analysis of Lotka’s law calculations, it is found that the value of C is 0,518 and the value of n was 1,717. The productivity equation for SCOPUS-indexed authors in Library Science journals for 2018–2022 was 0,518, which results in the number of author contributions in publishing one article being 51,84%. In addition, the results of the analysis show that Dmax was 0.280 with a critical value of 0,009. Conclusion. These findings indicate that Dmax is bigger than the crucial value and it does not follow Lotka's law.

Although research into entrepreneurship focuses on aspects inherent to entrepreneur's figure, universities of this nature and knowledge transfer, the main issue that still permeates it is the scarcity of scientific studies that explore the entrepreneurial nature of the productions in terms of quality, dissemination and measurement, linked to regional development. The aim of this article is to measure the entrepreneurial nature of knowledge through Lotka's law, in the regional development context. Considering bibliometry as the research's methodological tool, the investigation of the materials collected on the Web of Science and Scopus Elsevier bases was subdivided into performance analysis, scientific mapping, Lotka distribution and qualitative analysis of the most relevant productions. It was concluded that Lotka's distributional index, if in isolation way, has weaknesses in dealing with the entrepreneurship level applied to regional development, especially with regard to the concept abstraction applied to this nature in productions and its complexity in the perception and treatment of the variables that make it up. [ABSTRACT FROM AUTHOR]

Scientometric study on covid-19 has taken place to highlight the latest trend and situation of literature on covid-19. After the outbreak from Wuhan city, coronavirus spread over the world and that destroyed the whole health, mobility, livelihood and socio-economic management. To make a qualitative and quantitative investigation this scientometric study is eventuated. Thousands of research output are proliferating on this epidemic situation. During 18 months (2019 December-2021 May) WOS database indexed 1234 literature on covid-19 and related topics. Most of the publishers dropped their paywall and made it open access for more communication. To exact all secondary bibliographic data a string was created with a time span. For visualization and mapping, a .txt file has been downloaded from the WOS database. Some statistical formulas are adequate to calculate annual growth rate (AGR), author productivity, collaborative coefficient (CC). WOS viewers, MS Excel, QGIS, software also used for data representation. The outcome results are, the direction of literature growth map always upwards. In the top 10 journals and authors, ‘Medicine’ and ‘Wang J’ ranked top. Author collaboration was maximum (0.997) but more collaboration was required. China, India and the USA contributed the most with relevant research output. Covid-19 is near all subject disciplines, where medical science, environmental science, engineering and social science are gathered. It is hoped that this type of research outcome will help the government and society to manage and develop strategies for the future to prevent such natural disasters.

This article presents a bibliometric study on different types of risk and bankruptcy, aiming to contribute to academic knowledge in this area. We used the bibliometrix tools in R and VOSviewer, following the main laws of bibliometrics (Bradford's law, Lotka's law, and Zipf's law). We analyzed 7163 relevant academic publications retrieved from the WOS database between 1995 and 2023. The characterization of the literature identified trends, importance, and scientific relevance of works, journals, and authors. This allows for promoting collaborations among researchers and provides insights for strategic decision making, advancing knowledge in the field. The most relevant journal was the "Journal of Banking and Finance", with Edward Altman as the prominent author. The United States and China were the most active countries in research. The current research highlights terms such as "board size", "CRS", "responsibility", and "governance", which are commonly found in recent works. The themes of greatest centrality include risk, model, and debt. The bibliometric review revealed gaps in knowledge and research, indicating a growing trend of studies in this area. This article provides valuable information for researchers and managers, supporting decision making in risk management and bankruptcy. [ABSTRACT FROM AUTHOR]

This article aims to contribute to the academic knowledge in the field of scientific production regarding decision support tools for investments in the capital market, specifically focusing on fundamental analysis, technical analysis, and Ichimoku dynamics. Bibliometric analysis, following the three main laws (Bradford's Law, Lotka's Law, and Zipf's Law), was employed to evaluate scientific production, identify publication patterns, and uncover gaps and collaboration networks over the last thirty years. To achieve these objectives, 1710 relevant academic publications on the topic were analyzed and retrieved from the Web of Science (WOS) database, pertaining to the last 30 years, between 1990 and 22 May 2023. The significance of this article lies in the contributions of the findings, which advance scientific knowledge by identifying gaps in the knowledge and research, particularly in the limited literature on Ichimoku; our review reveals a growing trend of research in this area. Another notable conclusion is the emergence of new research topics and areas of interest, as well as the identification of collaboration networks among authors, institutions, and countries. Moreover, the article provides valuable insights for financial professionals and investors who are interested in applying these methodologies as methods for price forecasting. The highlighted results support investment decision making, trading strategies, and portfolio management. [ABSTRACT FROM AUTHOR]

We provide two examples of the appearance of heavy-tailed distributions in social sciences applications. Among these distributions are the laws of Pareto and Lotka and some new ones. The examples are illustrated through the construction of suitable toy models. [ABSTRACT FROM AUTHOR]

Objective: The primary objective of the current research is to compare Lotka's law of author productivity and the Google Scholar i10-Index with the number of authors and their articles in the field of chemistry in Iran indexed in the Web of Science (WoS) from 2000 to 2020. Materials and Methods: This study is a descriptive-qualitative type of research that was carried out using the scientometric approach. The statistical population of the present study consisted of all Iranian articles published in the field of chemistry indexed in the Science Citation Index Expanded. Some scientometric software packages were used to analyze the data with Lotka's law and i10-index. Results: The most prolific Iranian authors in chemistry were Mohamadreza Ganjali from the University of Tehran, Majid Heravi from Alzahra University, and Mojtaba Shamsipur from the Razi University of Kermanshah, all being acclaimed scientists in Iran. The results suggest that the validity of Lotka's law was not confirmed in measuring Iranian authors' productivity in the field of chemistry. However, it is hard to draw a negative conclusion about the validity of Lotka's law from a single experiment. Moreover, investigating the i10-index revealed that 85% of the Iranian authors with more than one publication have an i10-index. Conclusion: The results also indicated that the validity of Lotka's law cannot be confirmed, considering the Iranian chemistry papers indexed in the WoS. Furthermore, the results imply that the i10-index closely follows the authors with over one published paper and presents a high capability application in this field as a credible index. [ABSTRACT FROM AUTHOR]

Scientometric study on covid-19 has taken place to highlight the latest trend and situation of literature on covid-19. After the outbreak from Wuhan city, Coronavirus spread worldwide, destroying health, mobility, livelihood and socio-economic management. To make a qualitative and quantitative investigation this scientometric study is eventuated. Thousands of research outputs are increasing in this epidemic situation. During 18 months (2019 December-2021 May) WOS database indexed 1234 literature on covid-19 and related topics. Most of the publishers dropped their paywall and made it open access for more communication. A string was created with a time to exact all secondary bibliographic data. A .txt file has been downloaded from the WOS database for visualisation and mapping. Some statistical formulas are adequate to calculate the annual growth rate (AGR), author productivity, and collaborative coefficient (CC). WOS viewers, MS Excel, and QGIS software are also used for data representation. The outcome results are the direction of the literature growth map continuously upward. In the top 10 journals and authors, 'Medicine' and 'Wang J' ranked top. Author collaboration was maximum (0.997), but more collaboration was required. China, India and the USA contributed the most with relevant research output. Covid-19 is near all subject disciplines, where medical science, environmental science, engineering and social science are gathered. It is hoped that this type of research outcome will help the government and society manage and develop future strategies to prevent such natural disasters. [ABSTRACT FROM AUTHOR]

The purpose of our bibliometric research was to capture and analyze the trends of two types of well-known classical artificial intelligence (AI) algorithms: neural networks (NNs) and genetic algorithms (GAs). Symmetry is a very popular international and interdisciplinary scientific journal that cover six major research subjects of mathematics, computer science, engineering science, physics, biology, and chemistry which are all related to our research on classical AI algorithms; therefore, we referred to the most innovative research articles of classical AI algorithms that have been published in Symmetry, which have also introduced new advanced applications for NNs and Gas. Furthermore, we used the keywords of "neural network algorithm" or "artificial neural network" to search the SSCI database from 2002 to 2021 and obtained 951 NN publications. For comparison purposes, we also analyzed GA trends by using the keywords "genetic algorithm" to search the SSCI database over the same period and we obtained 878 GA publications. All of the NN and GA publication results were categorized into eight groups for deep analyses so as to investigate their current trends and forecasts. Furthermore, we applied the Kolmogorov–Smirnov test (K–S test) to check whether our bibliometric research complied with Lotka's law. In summary, we found that the number of applications for both NNs and GAs are continuing to grow but the use of NNs is increasing more sharply than the use of GAs due to the boom in deep learning development. We hope that our research can serve as a roadmap for other NN and GA researchers to help them to save time and stay at the cutting edge of AI research trends. [ABSTRACT FROM AUTHOR]

This research has the general objective to map the scientific production relative to the bibliometric studies indexed in the Reference Database of Journal Articles in Information Science. The methodology, in turn, is based on applied research typology, as of its nature; quantitative, regarding the problems approach; exploratory and descriptive about the goals; and bibliographic research, as for the procedures. For its achievement, it used a bibliometrics study at Brapci, from Lotka's, Bradford's, and Zipf's bibliometrics laws. The study analyzes 1,253 articles and its results demonstrate that: Maria Claudia Cabrini Grácio is the author who publishes the most about the said theme; on the other hand, the Universidade Federal do Rio Grande do Sul is the teaching institution with the highest productivity; concerning the co-authorship networks, the author Maria Claudia Cabrini Grácio stands out yet again. Furthermore, it was verified that the event that publishes the most about this theme is The Brazilian Meeting on Bibliometrics and Scientometrics, and the term bibliometrics is the word that better represents the theme explored. It was also identified that 2018 was the year with the most publications on bibliometrics. Lastly, it's concluded that the area of Information Science contributes significantly with relevant productions about bibliometrics, as well as presents the main scientific characteristics that permeate said productions. [ABSTRACT FROM AUTHOR]

The paper examines the possibility of applying higher degree numerical integration method upon Lotka’s distribution data. The widely used method applied here is Pao method which precisely calculate the value of the constant C and this is a very crucial and deterministic controlling factor to define the behaviour of the authors’ productivity distribution fitted to Lotka’s equation. Simpson’s 3/8 rule has been used to derive a new equation for the calculation of a much refined constant C and fitted to original Chemical Abstract and Auerbach data. [ABSTRACT FROM AUTHOR]

Background: This study presents a comprehensive review of blockchain technology with a sustainability orientation in supply chains and logistics. Methods: The publications are extracted from the Scopus and Web of Science databases, comprising 552 publications between 2017 and 2022. Several bibliometric laws and techniques, namely three-field analysis, Bradford's Law, Lotka's Law, and thematic maps, are applied in R with the bibliometrix package. Content analysis is also carried out based on 185 publications to appreciate the industry-based view of the field. Results: The bibliometric results indicate that this field is on the rise. Authors, sources, affiliations, countries, keywords, and their relationships are also addressed. The findings of the content analysis and thematic maps reveal that some of the most highlighted themes in the literature include traceability, COVID-19, the internet of things, and Industry 4.0. The most popular industry in this field is discovered to be food and agriculture. Conclusions: This paper contributes to the still relatively scarce literature on how blockchain technology fosters sustainable supply chains and logistics, providing a closer look at blockchain use, methodologies, and future directions for different industries concerning food, agriculture, fashion, textile and apparel, manufacturing, automotive, maritime and shipping, healthcare and pharmaceutical, mining and mineral, and energy. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Administraçãao da UNIMEP is the property of Revista de Administracao da UNIMEP and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

There is a great deal of disparity in the creation and dissemination of scholarly publications across disciplines. The main objective of the study in this article is three-fold: first, to find empirical evidence of publishing regularity in economics journals in India; second, to examine what accounts for author concentration in journals, with a special focus on economics; and third, to understand the nature of scholarly collaboration. For this, authorship data from eight Indian economics journals and the Economic and Political Weekly (EPW), a prestigious periodical encompassing a range of areas in social sciences, were manually obtained. This study contributes to existing literature by substantiating that author concentration is not merely an outcome of the degree of journal specialization. Interestingly, the study shows that a journal with generic readership is likely to form a power-law distribution. The computed measures of social network analysis indicate that collaboration in Indian economics, unlike in world economics, is in a nascent stage, consisting of a large number of isolated authors on the one hand, and some fragmented groups of varied sizes, on the other. [ABSTRACT FROM AUTHOR]

This article aims to contribute to the academic knowledge in the field of scientific production regarding decision support tools for investments in the capital market, specifically focusing on fundamental analysis, technical analysis, and Ichimoku dynamics. Bibliometric analysis, following the three main laws (Bradford’s Law, Lotka’s Law, and Zipf’s Law), was employed to evaluate scientific production, identify publication patterns, and uncover gaps and collaboration networks over the last thirty years. To achieve these objectives, 1710 relevant academic publications on the topic were analyzed and retrieved from the Web of Science (WOS) database, pertaining to the last 30 years, between 1990 and 22 May 2023. The significance of this article lies in the contributions of the findings, which advance scientific knowledge by identifying gaps in the knowledge and research, particularly in the limited literature on Ichimoku; our review reveals a growing trend of research in this area. Another notable conclusion is the emergence of new research topics and areas of interest, as well as the identification of collaboration networks among authors, institutions, and countries. Moreover, the article provides valuable insights for financial professionals and investors who are interested in applying these methodologies as methods for price forecasting. The highlighted results support investment decision making, trading strategies, and portfolio management.

We provide two examples of the appearance of heavy-tailed distributions in social sciences applications. Among these distributions are the laws of Pareto and Lotka and some new ones. The examples are illustrated through the construction of suitable toy models.

Copyright of TECHNO Review is the property of Eurasia Academic Publishing Group and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background and Aim: Psycho-oncology is a cross-disciplinary and collaborative sub-specialty of oncology that focuses on the psychological, behavioral, ethical, and social aspects of cancer in clinical settings. The aim of this bibliometric study was to analyze and characterize the research productivity and trends in psycho-oncology between 1980 and 2021. Methodology: In May 2022, the Scopus® database was searched for psycho-oncology-related publications using predetermined search keywords with specific restrictions. Lotka’s law was applied to check the authors’ productivity, while Bradford’s law was used to assess the core journals in this field. The data was analyzed for different bibliometric indicators in the Biblioshiny package, an RStudio tool for bibliometric analysis. Results: The initial search resulted in a total of 2,906 publications. Of which, 1,832 publications were included in the final analysis, published between 1980 and 2021. The analyzed publications were written by 7,363 authors from 74 countries and published in 490 journals. There has been a significant increase in psycho-oncology-related publications after 2010. The most productive year was 2021 (n = 365). The annual scientific growth rate was found to be 13.9%. The most relevant leading author in terms of publications was Luigi Grassi from the University of Ferrara, Italy (n = 42). Lotka’s law found that the number of authors declined as the number of papers written increased. The core journals were Psycho-Oncology, Supportive Care in Cancer, and Journal of Psychosocial Oncology. The most frequently used author’s keywords other than searching keywords were cancer, oncology, quality of life, depression, and anxiety. Recent psycho-oncology-related topics included mental health, COVID-19 infection in humans, people, pandemic, and tumor. The University of Sydney was the top-ranked institution. The leading country in terms of publications, citations, corresponding author country, and international collaboration was the United States of America (United States). The United States had the strongest collaboration with Australia and Canada. Conclusion: The research hotspots include mental health conditions and interventions in cancer patients. We identified international collaboration and research expenditure to be strongly associated with psycho-oncology research productivity. Researchers’ collaboration, which is visible among developed countries, should be extended to low-income countries in order to expand psycho-oncology-related research and understanding. [ABSTRACT FROM AUTHOR]

Our study is a comprehensive examination of the existing literature pertaining to algorithmic trading and its temporal progression in a framework driven by technology development. A total of 4552 papers were analyzed, spanning the period from 1990 to 2023. Performance metrics evaluation and science mapping approaches were utilized in this study. The data was obtained from the Scopus database, and the analysis was conducted using the Biblioshiny environment. The research landscape has undergone significant changes in recent years due to advancements in data-driven technology and the implementation of sophisticated algorithms such as machine learning, deep learning, and genetic algorithms. The shift in research interest has been particularly pronounced in the last decade compared to earlier periods. The most significant contribution in terms of production is associated with authors who are affiliated with the People's Republic of China. Another significant discovery is the limited knowledge dissemination and collaboration among scholars, as seen by the examination of co-authorship in academic papers. In relation to the conceptual framework of the study domain, we have identified two primary trajectories, specifically financial markets, and energy markets, whereby the utilization of deep learning techniques has garnered significant attention. • Global interest in algorithmic trading is surging, evidenced by a steady increase in published research. • Machine learning and deep learning technologies are transforming financial and energy markets. • Key areas are portfolio optimization, high-frequency trading, machine learning applications, and transaction optimization. • Algorithmic trading expands beyond traditional finance to environmental sustainability, energy management, and blockchain. • Lack of researcher collaboration suggests a chance to share knowledge and progress science. [ABSTRACT FROM AUTHOR]

Background and AimPsycho-oncology is a cross-disciplinary and collaborative sub-specialty of oncology that focuses on the psychological, behavioral, ethical, and social aspects of cancer in clinical settings. The aim of this bibliometric study was to analyze and characterize the research productivity and trends in psycho-oncology between 1980 and 2021.MethodologyIn May 2022, the Scopus® database was searched for psycho-oncology-related publications using predetermined search keywords with specific restrictions. Lotka’s law was applied to check the authors’ productivity, while Bradford’s law was used to assess the core journals in this field. The data was analyzed for different bibliometric indicators in the Biblioshiny package, an RStudio tool for bibliometric analysis.ResultsThe initial search resulted in a total of 2,906 publications. Of which, 1,832 publications were included in the final analysis, published between 1980 and 2021. The analyzed publications were written by 7,363 authors from 74 countries and published in 490 journals. There has been a significant increase in psycho-oncology-related publications after 2010. The most productive year was 2021 (n = 365). The annual scientific growth rate was found to be 13.9%. The most relevant leading author in terms of publications was Luigi Grassi from the University of Ferrara, Italy (n = 42). Lotka’s law found that the number of authors declined as the number of papers written increased. The core journals were Psycho-Oncology, Supportive Care in Cancer, and Journal of Psychosocial Oncology. The most frequently used author’s keywords other than searching keywords were cancer, oncology, quality of life, depression, and anxiety. Recent psycho-oncology-related topics included mental health, COVID-19 infection in humans, people, pandemic, and tumor. The University of Sydney was the top-ranked institution. The leading country in terms of publications, citations, corresponding author country, and international collaboration was the United States of America (United States). The United States had the strongest collaboration with Australia and Canada.ConclusionThe research hotspots include mental health conditions and interventions in cancer patients. We identified international collaboration and research expenditure to be strongly associated with psycho-oncology research productivity. Researchers’ collaboration, which is visible among developed countries, should be extended to low-income countries in order to expand psycho-oncology-related research and understanding.

Digital curation is an area of research whose relevance has grown due to the increase in digital information. This article analyzes the scientific output about digital curation indexed on Scopus database from 2010 to 2020. It collects 334 references from Scopus documents and uses the software Bibliometrix and VOSViewer. It analyses the results related to production, connection and citation indicators, like: documents' typology, temporal evolution, Lotka's law, authors that are more productive and their impact, Bradford's law, sources of publication with more impact, keywords used by the authors and their cooccurrence network, and co-quotation analysis. It concludes that digital curation is an interdisciplinary area with vast research possibilities. The results offer a partial overview of digital curation capable of helping researchers to have a starting point and understand the stage of development of the theme. [ABSTRACT FROM AUTHOR]

In this paper, we analyzed systematically the doctoral research works produced by Indian Universities in the discipline of Library and Information Science (LIS). This study aims to find out the developmental pattern, current trends, popular focused areas, most productivity universities, and supervisors, as well as language and gender-wise productivity of LIS theses. Based on two Indian data sources a database was developed on LIS doctoral research and inferences were drawn as per the research questions formulated. It was observed that altogether 957 doctoral theses have been guided by 382 supervisors from 105 universities in India. Lotka's law of scientific productivity was applied for the first of it's kind to the 'guide-ship pattern of doctoral works' and found validated. Five broad areas of research are found to be the most focused themes of Indian LIS research. This paper highlights the evolution and pattern of LIS research to identify the areas that have influenced the scholars most and to know the direction of research. [ABSTRACT FROM AUTHOR]

In this study, we examined the applicability of Lotka's law by reviewing 590 STEM librarianship research articles published in seven journals between 2016 and 2019. Our analysis suggests that the frequency distribution of scientific productivity in the field of STEM librarianship does not comply with Lotka's law, with fewer authors writing more than one research article than expected. [ABSTRACT FROM AUTHOR]

Since the emergence of the novel Coronavirus disease from Wuhan, China, in early December 2019, scientists every where in the world have focused on this infection to find a way to deal with it. Due to the rapid growth in the literature on this disease, the WHO took the initiative to collate the emerging publications and created "WHO COVID-19 Database". A scientometric study was conducted to better understand the nature of medical literature on COVID-19 included in the WHO COVID-19 Database, and this article aims to provide an analysis of the coverage of those publications focusing on the twelve months, from December 2019 to November 2020. A total of 35,791 full-text research articles on Coronavirus infections has been published across the world. These publications were originated from 57 countries, indicating the international spread of COVID-19 research. The USA was the largest contributor with 12,989 articles, followed by UK and Netherlands. All the publications mentioned above are written in 15 different languages where English has become the dominant language out of all those languages with 93.25%. According to the findings, the co-authorship network of 3 authors Eric J. Rubin, Lindsey R. Baden and Stephen Morrissey has made the highest contribution with 34 papers published in the New England Journal of Medicine (N Engl J Med). The journal with the highest number of publications on COVID-19 research was the International Journal of Environmental Research and Public Health (Int. J. Environ. Res. Public Health - online). The classification of study type reveals that the maximum number of articles are published on risk factors. This study showed that core journals publishing COVID-19 research are scattered among journals, closely conforming to Bradford's Law of scattering. The Lotka's Law on authorship productivity has been tested to confirm the law's applicability to the present dataset. According to the test, there is a variation of author productivity between the observed percentage and expected percentage of authors as in Lotka's Law. This study will help the research community to get the required information for their research. Further, the information in this paper will encourage the researchers in finding more facts on COVID-19. [ABSTRACT FROM AUTHOR]

The study examines 1220 digital library research papers published by BRICS countries during the period 2000 to 2019. Bibliographic data on the research papers were collected from Web of Science database. It is found that maximum number of publications (225) were two-authored. The Degree of collaboration is 0.84, collaborative index is 4.14, the collaboration co-efficient is 0.59 and the modified collaboration co-efficient is 0.61. Among all the BRICS countries, China has contributed the most number of papers [690 (56.58%)] followed by India with 205 (16.80%) contributions. Lotka's law was not found to fit with the observed author's productivity of the study. The study concludes that there is increased research on digital library in BRICS countries. [ABSTRACT FROM AUTHOR]

An attempt is made to examine the authorship distribution in Synthetic Biology (SB) literature and to validate Lotka's law of author productivity. Authors obtained data for this study from the WOS database. A total of 12012 papers with 33151 unique authors has identified, and used for further analysis. Authors calculated the exponents "n" and "c". Researchers employed Kolmogorov-Smirnov (K-S) test of goodness-of-fit to verify the validity of Lotka's Law in SB literature. The results of this study proved that Lotka's Law of author productivity does fit with SB literature based on the calculated values n = -2.45 and c= 0.74. [ABSTRACT FROM AUTHOR]

The Study examines the Biodiversity in India as revealed in the database of web of science in the year of 1991-2017. It was seen that the analysis included author productivity, authorship pattern, degrees of collaboration, year wise Cited references, Relative growth rate, and doubling time. This study also verified Lotka's Inverse square law of author productivity, Price's Square root law, Pareto Principle (80*20 Rule). [ABSTRACT FROM AUTHOR]

This article focuses on a central goal which lies in the approach of Moroccan literary production written in Arabic, published during the period from 1929 to 1999. It aims to represent and analyze the various extensions of its structures, whether related to its producers, components of publication, or parallel circulation. With this in mind, the article shows up aspects of variation, at levels of distribution of production within different literary genres, as well as components of producers' structures, distribution of the contribution of publishing structures and the nature of their components. These variations keep certain limits of interconnection. They also remain under the terms of literary and socio-cultural conditions, concerning the specificities of literary genres and the conditions and contexts of their evolution. [ABSTRACT FROM AUTHOR]