Pub Date : 2023-04-17DOI: 10.5530/jscires.12.1.005
Jay Vineshbhai Tailor, R. Tailor
For stable functioning of an urban area, a balance between natural resources, urban infrastructure, and population is very much required. That’s where concept of carrying capacity comes into the picture to find out limitation and current overloading on natural resources and urban infrastructure. In this study to understand growth of research work on Urban Carrying Capacity (UCC) from seed to tree, a thorough bibliometric analysis has been done in R language-based software package called Biblioshiny which is an online web-based data analysis framework. Analysis has been done for the time span of 1978 to 2021, from which 327 manually filtered documents have been selected. The results show that (1) since 1978, papers on UCC are gradually increasing. This time span is divided into low production period, stable production period and rapid production period (2) UCC research covers 28 countries, out of which China, Indonesia and USA are the top three. In which China is having the most number of papers and collaboration with other countries (3) Sustainable development, ecological carrying capacity, ecological footprint, environment carrying capacity, water resources and analytical hierarchy process are the high-frequency keywords used in recent years (4) Mostly papers are focused on single factors based studies (land-based, water-based, air-based, infrastructure-based) and low numbers papers are on comprehensive analysis. Finally, study conclude that future scope on UCC includes strengthening existing definition and theory of carrying capacity, introducing new technology and model in the system like artificial intelligence, work on more comprehensive analysis than single-factor analysis and constructing a practical planning policy.
{"title":"Bibliometric Analysis of Urban Carrying Capacity: History, Current Status, Development and Future Direction","authors":"Jay Vineshbhai Tailor, R. Tailor","doi":"10.5530/jscires.12.1.005","DOIUrl":"https://doi.org/10.5530/jscires.12.1.005","url":null,"abstract":"For stable functioning of an urban area, a balance between natural resources, urban infrastructure, and population is very much required. That’s where concept of carrying capacity comes into the picture to find out limitation and current overloading on natural resources and urban infrastructure. In this study to understand growth of research work on Urban Carrying Capacity (UCC) from seed to tree, a thorough bibliometric analysis has been done in R language-based software package called Biblioshiny which is an online web-based data analysis framework. Analysis has been done for the time span of 1978 to 2021, from which 327 manually filtered documents have been selected. The results show that (1) since 1978, papers on UCC are gradually increasing. This time span is divided into low production period, stable production period and rapid production period (2) UCC research covers 28 countries, out of which China, Indonesia and USA are the top three. In which China is having the most number of papers and collaboration with other countries (3) Sustainable development, ecological carrying capacity, ecological footprint, environment carrying capacity, water resources and analytical hierarchy process are the high-frequency keywords used in recent years (4) Mostly papers are focused on single factors based studies (land-based, water-based, air-based, infrastructure-based) and low numbers papers are on comprehensive analysis. Finally, study conclude that future scope on UCC includes strengthening existing definition and theory of carrying capacity, introducing new technology and model in the system like artificial intelligence, work on more comprehensive analysis than single-factor analysis and constructing a practical planning policy.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"1 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91393748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-17DOI: 10.5530/jscires.12.1.017
Anindya Basu, Bidyarthi Dutta
{"title":"Redesigning of Lotka’s Law with Simpson’s 3/8 Rule","authors":"Anindya Basu, Bidyarthi Dutta","doi":"10.5530/jscires.12.1.017","DOIUrl":"https://doi.org/10.5530/jscires.12.1.017","url":null,"abstract":"","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"32 5","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72448040","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-17DOI: 10.5530/jscires.12.1.018
Jung-Chol Jo, Jin-Bom Jong, V. Drakopoulos, SONG-IL Ri
{"title":"A Methodology for Strategic Selection of Priority Research Topics in Terms of Bibliometric Analysis","authors":"Jung-Chol Jo, Jin-Bom Jong, V. Drakopoulos, SONG-IL Ri","doi":"10.5530/jscires.12.1.018","DOIUrl":"https://doi.org/10.5530/jscires.12.1.018","url":null,"abstract":"","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"51 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79388826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-17DOI: 10.5530/jscires.12.1.012
I. Sameer, Walid Simmou, M. Ibrahim
This study used scientometrics to map CSR/EM knowledge, including yearly publications, most cited nations, journals, institutions, significant themes, and developing trends. We used Scopus data to retrieved on August 1, 2021. The search term was "CSR/EM" in the title, abstract, and author's keywords. This analysis used VOSviewer. We found that Journal of Cleaner Production was the top productive and influential journal in a study of 1,974 publications on CSR/EM. The American University of Beirut and the University of Derby are the prolific institutions. The United Kingdom is the most productive country, and the most commonly used terms include emerging economy, corporate social responsibility, and sustainability. The circular economy, financial performance, sustainable development objectives, and entrepreneurship are possible feasible research themes. The amount of CSR/EM publications related to business is quite large and continues to grow at a fast rate. According to the keyword analysis, CSR/EM has had a major impact on all developing economies.
{"title":"Mapping the Intellectual Structure Corporate Social Responsibility in Emerging Market: A Scientometric Analysis from 1984 to 2021","authors":"I. Sameer, Walid Simmou, M. Ibrahim","doi":"10.5530/jscires.12.1.012","DOIUrl":"https://doi.org/10.5530/jscires.12.1.012","url":null,"abstract":"This study used scientometrics to map CSR/EM knowledge, including yearly publications, most cited nations, journals, institutions, significant themes, and developing trends. We used Scopus data to retrieved on August 1, 2021. The search term was \"CSR/EM\" in the title, abstract, and author's keywords. This analysis used VOSviewer. We found that Journal of Cleaner Production was the top productive and influential journal in a study of 1,974 publications on CSR/EM. The American University of Beirut and the University of Derby are the prolific institutions. The United Kingdom is the most productive country, and the most commonly used terms include emerging economy, corporate social responsibility, and sustainability. The circular economy, financial performance, sustainable development objectives, and entrepreneurship are possible feasible research themes. The amount of CSR/EM publications related to business is quite large and continues to grow at a fast rate. According to the keyword analysis, CSR/EM has had a major impact on all developing economies.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"52 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87475132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-17DOI: 10.5530/jscires.12.1.008
Galal M. Bin Makhashen, Hamdi A. Al-Jamimi
Highly cited articles capture the attention of significant contributors in the research community as an opportunity to improve knowledge, source of ideas or solutions, and advance their research in general. Typically, these articles are authored by a large number of scientists with international collaboration. However, this could not be the only reason for an article to be highly cited, there might be several other characteristics for an article to be more attractive to researchers and readers. In other words, there are a few other characteristics that help articles/papers to be more than others to appear in search engines or to grab readers’ attention. In this study, we modeled several machine-learning methods with a set of articles, and journal characteristics including authors-count, title characteristics, abstract length, international collaboration, number of keywords, funding information, journal characteristics, etc. We extracted 20 characteristics and developed multiple machine-learning models to automate highly-cited papers recognition from regular papers. In experiments conducted with an ensemble machine learning algorithm, 97% recognition accuracy was achieved. Other algorithms including a deep learning method using LSTMs also achieved high recognition accuracy. Such high performances can be utilized for a promising HCP auto-detection system in the future.
{"title":"An Intelligent Prediction of the Next Highly Cited Paper Using Machine Learning","authors":"Galal M. Bin Makhashen, Hamdi A. Al-Jamimi","doi":"10.5530/jscires.12.1.008","DOIUrl":"https://doi.org/10.5530/jscires.12.1.008","url":null,"abstract":"Highly cited articles capture the attention of significant contributors in the research community as an opportunity to improve knowledge, source of ideas or solutions, and advance their research in general. Typically, these articles are authored by a large number of scientists with international collaboration. However, this could not be the only reason for an article to be highly cited, there might be several other characteristics for an article to be more attractive to researchers and readers. In other words, there are a few other characteristics that help articles/papers to be more than others to appear in search engines or to grab readers’ attention. In this study, we modeled several machine-learning methods with a set of articles, and journal characteristics including authors-count, title characteristics, abstract length, international collaboration, number of keywords, funding information, journal characteristics, etc. We extracted 20 characteristics and developed multiple machine-learning models to automate highly-cited papers recognition from regular papers. In experiments conducted with an ensemble machine learning algorithm, 97% recognition accuracy was achieved. Other algorithms including a deep learning method using LSTMs also achieved high recognition accuracy. Such high performances can be utilized for a promising HCP auto-detection system in the future.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"9 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75269810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
F. Nisha, Sunil Kumar, Shipra Awasthi, M. Tripathi
High number of citations of research publications expresses its intellectual and cognitive impact. Papers with high citations are considered as a landmark in relevant research field as these express trends and emerging research areas as well as set future course of research. The objective of this study is to conduct bibliometric analysis of the top 100 most cited studies in the discipline of Information Science and Library Science. The data for the study was obtained from “Information Science and Library Science” category of Web of Science, as indexed in the last twenty-one years (2000-2021). The outcome of bibliometric analysis included progressive growth in citation over time, annual citation density, name of journal with its impact factor, which published these papers, year of publication, type of article i.e. articles, proceedings, book reviews, reviews and poetry etc; nature of access i.e. subscribed or open access, and country of origin. Number of citations of these papers as reported by Web of Science were cross checked with numbers of citations reported by Google Scholar to understand which one provided higher number of citations for the same paper. The number of citations in the top 100 cited papers ranged from 699 to14,273. The large numbers of the top 100 cited papers were published in MIS Quarterly. There were 40 publications authored by two, while 13 other papers were authored by more than four authors. This research is valuable for scholars in the discipline of library science and information science in identifying highly cited papers in the last 21 years, frequently pursued research areas, and names of journals publishing high quality research work in library Science discipline. The study of frequently cited papers will also guide in designing of objectives and methodology of future research studies. Journals have been charging very high subscription fee. This study will also help librarian in identifying journals which are making valuable contributions in the discipline of Information and Library Science.
研究出版物的大量引用表明其对智力和认知的影响。高被引论文被认为是相关研究领域的里程碑，因为这些论文表达了研究趋势和新兴研究领域，并确定了未来的研究方向。本研究的目的是对信息学与图书馆学学科中被引次数最多的前100篇论文进行文献计量分析。本研究的数据来源于Web of Science的“信息科学与图书馆学”分类，索引时间为近21年(2000-2021)。文献计量分析的结果包括引文随时间的递进增长、年度引文密度、发表这些论文的期刊名称及其影响因子、出版年份、文章类型(即文章、论文集、书评、评论和诗歌等);获取的性质，即订阅或开放获取，以及原产国。我们将Web of Science报告的这些论文的引用次数与Google Scholar报告的引用次数进行交叉核对，以了解哪一篇论文的引用次数更高。排名前100的论文被引次数从699次到14273次不等。被引前100名的论文大部分发表在MIS季刊上。有40篇论文是由两人共同撰写的，另有13篇论文是由4人以上共同撰写的。本研究对图书馆学与情报学领域的学者识别近21年来高被引论文、频繁被引的研究领域和发表高质量研究成果的图书馆学学科期刊名称具有重要的参考价值。对经常被引论文的研究也将指导未来研究目标和方法的设计。期刊收取很高的订阅费。本研究亦有助图书馆馆员甄别在情报与图书馆学领域有贡献的期刊。
{"title":"Top 100 cited papers in Information and Library science: A Brief Analysis","authors":"F. Nisha, Sunil Kumar, Shipra Awasthi, M. Tripathi","doi":"10.5530/jscires.11.3.40","DOIUrl":"https://doi.org/10.5530/jscires.11.3.40","url":null,"abstract":"High number of citations of research publications expresses its intellectual and cognitive impact. Papers with high citations are considered as a landmark in relevant research field as these express trends and emerging research areas as well as set future course of research. The objective of this study is to conduct bibliometric analysis of the top 100 most cited studies in the discipline of Information Science and Library Science. The data for the study was obtained from “Information Science and Library Science” category of Web of Science, as indexed in the last twenty-one years (2000-2021). The outcome of bibliometric analysis included progressive growth in citation over time, annual citation density, name of journal with its impact factor, which published these papers, year of publication, type of article i.e. articles, proceedings, book reviews, reviews and poetry etc; nature of access i.e. subscribed or open access, and country of origin. Number of citations of these papers as reported by Web of Science were cross checked with numbers of citations reported by Google Scholar to understand which one provided higher number of citations for the same paper. The number of citations in the top 100 cited papers ranged from 699 to14,273. The large numbers of the top 100 cited papers were published in MIS Quarterly. There were 40 publications authored by two, while 13 other papers were authored by more than four authors. This research is valuable for scholars in the discipline of library science and information science in identifying highly cited papers in the last 21 years, frequently pursued research areas, and names of journals publishing high quality research work in library Science discipline. The study of frequently cited papers will also guide in designing of objectives and methodology of future research studies. Journals have been charging very high subscription fee. This study will also help librarian in identifying journals which are making valuable contributions in the discipline of Information and Library Science.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"01 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80093412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Book Review: Technology Business Incubator Process and Performance","authors":"Ganesaraman K","doi":"10.5530/jscires.11.3.51","DOIUrl":"https://doi.org/10.5530/jscires.11.3.51","url":null,"abstract":"","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"11 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81682658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The goal of this research is to examine the research approaches and trends in Korean popular music (K-pop). This bibliometric study is based on data from the Scopus database over the last ten years (2011–2021). This study examined 327 publications to determine the most prolific nations, authors, organizations, and referenced publications. The most active research publications were discovered to be in South Korea, the United States, and Australia. The most prolific institution has been recognized as Seoul National University (South Korea). The most influential author was determined to be Jin D.Y. Keyword co-occurrence analysis, author and country co-authorship analysis, and bibliographic coupling of documents utilizing the most widely used open-source information visualization technologies. The most productive magazines for K-pop are Kritika Kultura and the International Journal of Communication. This article summarizes the evolution of K-pop research and provides stakeholders with a concise overview of relevant studies and applications of K-pop. To our knowledge, this is the first study of its sort to do a Scopus-based mapping of the ‘K-pop and research’ literature. This will help develop the central theme and establish the scholars’ future research directions.
{"title":"Global Research Trend of Korean Popular Music: A Bibliometric Analysis","authors":"Wirapong Chansanam, Kornwipa Poonpon, Yuttana Jaroenruen, Nattapong Kaewboonma","doi":"10.5530/jscires.11.3.45","DOIUrl":"https://doi.org/10.5530/jscires.11.3.45","url":null,"abstract":"The goal of this research is to examine the research approaches and trends in Korean popular music (K-pop). This bibliometric study is based on data from the Scopus database over the last ten years (2011–2021). This study examined 327 publications to determine the most prolific nations, authors, organizations, and referenced publications. The most active research publications were discovered to be in South Korea, the United States, and Australia. The most prolific institution has been recognized as Seoul National University (South Korea). The most influential author was determined to be Jin D.Y. Keyword co-occurrence analysis, author and country co-authorship analysis, and bibliographic coupling of documents utilizing the most widely used open-source information visualization technologies. The most productive magazines for K-pop are Kritika Kultura and the International Journal of Communication. This article summarizes the evolution of K-pop research and provides stakeholders with a concise overview of relevant studies and applications of K-pop. To our knowledge, this is the first study of its sort to do a Scopus-based mapping of the ‘K-pop and research’ literature. This will help develop the central theme and establish the scholars’ future research directions.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"42 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75621851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The purpose of this study was to identify the citation status of scientific and research journals in the field of Information Science and Knowledge during the years 2016-2018. The present study is a survey analytic one and its statistical population includes all the articles of twelve scientific and research journals published by the National Scientific Journals Commission. Since some articles did not have a number of citations, out of 2264 citations, 1111 citations were analysed. The results showed that there was no statistically significant difference between source citation error and citation source language components, year of publication, number of authors, and author’s academic rank. But it has a significant relationship with the type of citation and publication component. The results showed that out of 1111 citations selected, 21 citations (1.9%) were not retrieved, 749 citations (67.4%) lacked any citations errors and 341 citations (30.7%) contained citations errors. The National Library of Librarian Studies and Information Organization and the Journal of Library and Information Research were the best in terms of citation accuracy, and the Journal of Human Interaction and Information had the lowest citation accuracy. Among the factors contributing to the occurrence of citation errors can be the lack of co-operation between authors, the carelessness of authors, and the lack of emphasis on journals. Solutions such as highlighting journals are recommended for authors to observe the validity of citations, insert proper citations to published articles, and evaluate and review some of the paper citations as an acceptance process.
{"title":"Study on Citation Accuracy of Iranian Journals in the Field of Library and Information Science","authors":"Yasin Veisi, A. Asnafi","doi":"10.5530/jscires.11.3.42","DOIUrl":"https://doi.org/10.5530/jscires.11.3.42","url":null,"abstract":"The purpose of this study was to identify the citation status of scientific and research journals in the field of Information Science and Knowledge during the years 2016-2018. The present study is a survey analytic one and its statistical population includes all the articles of twelve scientific and research journals published by the National Scientific Journals Commission. Since some articles did not have a number of citations, out of 2264 citations, 1111 citations were analysed. The results showed that there was no statistically significant difference between source citation error and citation source language components, year of publication, number of authors, and author’s academic rank. But it has a significant relationship with the type of citation and publication component. The results showed that out of 1111 citations selected, 21 citations (1.9%) were not retrieved, 749 citations (67.4%) lacked any citations errors and 341 citations (30.7%) contained citations errors. The National Library of Librarian Studies and Information Organization and the Journal of Library and Information Research were the best in terms of citation accuracy, and the Journal of Human Interaction and Information had the lowest citation accuracy. Among the factors contributing to the occurrence of citation errors can be the lack of co-operation between authors, the carelessness of authors, and the lack of emphasis on journals. Solutions such as highlighting journals are recommended for authors to observe the validity of citations, insert proper citations to published articles, and evaluate and review some of the paper citations as an acceptance process.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"52 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90549382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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