Pub Date : 2023-11-30DOI: 10.5530/jscires.12.3.066
D. Luong, Xuan-An Nguyen, Thanh-Thuy Ngo, My Ngoc Tran, Hong Lien Nguyen
{"title":"Social Media in General Education: A Bibliometric Analysis of Web of Science from 2005-2021","authors":"D. Luong, Xuan-An Nguyen, Thanh-Thuy Ngo, My Ngoc Tran, Hong Lien Nguyen","doi":"10.5530/jscires.12.3.066","DOIUrl":"https://doi.org/10.5530/jscires.12.3.066","url":null,"abstract":"","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139200924","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 : 2023-11-30DOI: 10.5530/jscires.12.3.056
Kaushikkumar P. Sheladiya, Chetan R Patel
Speedy technological, social, political, demographic, and urban developments continued to change the scale of the cities worldwide. Therefore, it becomes essential to model urban growth to minimize future uncertainties. Therefore, it is critical to investigate how cities grow and how researchers investigate which factors influence city growth. Using bibliometric methods, this study intends to pinpoint the publishing patterns and expansion potential of Urban Growth Modelling (UGM) works, providing a better understanding and possible future research paths. All published articles on the 'Urban Growth model' from Scopus were identified and analyzed using the Bibliometric R-package and VOSviewer software. 218 publications were identified from 1983 to 2023, published in 103 journals, and 25 book chapters contributed by 557 authors, with a 2.7 collaboration Index and 2.56 authors per document. The high-frequency keywords used in recent years are urban growth, land use, remote sensing, urban planning, cellular automaton, urban development, modeling, urbanization, Geographic Information System (GIS), and land use change. Research papers published in Computers, Environment, and Urban Systems are the most cited, with 1047 total citations, h -index 13. The most active country was China, with a total of 38 documents. The most cited paper for UGM research is titled 'Modelling urban growth in Atlanta using logistic regression', which received over 378 citations. The study's findings offer milestones, a starting point for important research productivity data, and an understanding of how UGM research has evolved. This will help to estimate and assess the rate of urbanization, its location, and the consequences of before and after development before it gets stranded in unsuitable and unsustainable pathways.
{"title":"Leveraging Urban Growth Models (UGM) for Sustainable Urban Planning and Climate Resilient Cities: A Bibliometric Analysis","authors":"Kaushikkumar P. Sheladiya, Chetan R Patel","doi":"10.5530/jscires.12.3.056","DOIUrl":"https://doi.org/10.5530/jscires.12.3.056","url":null,"abstract":"Speedy technological, social, political, demographic, and urban developments continued to change the scale of the cities worldwide. Therefore, it becomes essential to model urban growth to minimize future uncertainties. Therefore, it is critical to investigate how cities grow and how researchers investigate which factors influence city growth. Using bibliometric methods, this study intends to pinpoint the publishing patterns and expansion potential of Urban Growth Modelling (UGM) works, providing a better understanding and possible future research paths. All published articles on the 'Urban Growth model' from Scopus were identified and analyzed using the Bibliometric R-package and VOSviewer software. 218 publications were identified from 1983 to 2023, published in 103 journals, and 25 book chapters contributed by 557 authors, with a 2.7 collaboration Index and 2.56 authors per document. The high-frequency keywords used in recent years are urban growth, land use, remote sensing, urban planning, cellular automaton, urban development, modeling, urbanization, Geographic Information System (GIS), and land use change. Research papers published in Computers, Environment, and Urban Systems are the most cited, with 1047 total citations, h -index 13. The most active country was China, with a total of 38 documents. The most cited paper for UGM research is titled 'Modelling urban growth in Atlanta using logistic regression', which received over 378 citations. The study's findings offer milestones, a starting point for important research productivity data, and an understanding of how UGM research has evolved. This will help to estimate and assess the rate of urbanization, its location, and the consequences of before and after development before it gets stranded in unsuitable and unsustainable pathways.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139207108","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 : 2023-11-30DOI: 10.5530/jscires.12.3.069
Suman Phalswal
{"title":"Mapping the Grassroots Innovation Research: A Bibliometric Analysis and Future Agenda","authors":"Suman Phalswal","doi":"10.5530/jscires.12.3.069","DOIUrl":"https://doi.org/10.5530/jscires.12.3.069","url":null,"abstract":"","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139199207","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 : 2023-11-30DOI: 10.5530/jscires.12.3.051
M. Kassim, M. Azra, F. Lananan, Mohd Iqbal Mohd Noor, Min Pau Tan, Yeong Yik Sung, Mazlan Abd Ghaffar
Climate change, a global challenge and among one of the significant keyword(s) that potentially attract various fields of studies to be performed. Assessing its changes in various types of analysis such as in terms of bibliometrics illustrate the importance of considering its global impacts
{"title":"Climate Change Research in Malaysia: A Scientometric Analysis","authors":"M. Kassim, M. Azra, F. Lananan, Mohd Iqbal Mohd Noor, Min Pau Tan, Yeong Yik Sung, Mazlan Abd Ghaffar","doi":"10.5530/jscires.12.3.051","DOIUrl":"https://doi.org/10.5530/jscires.12.3.051","url":null,"abstract":"Climate change, a global challenge and among one of the significant keyword(s) that potentially attract various fields of studies to be performed. Assessing its changes in various types of analysis such as in terms of bibliometrics illustrate the importance of considering its global impacts","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139203130","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 : 2023-11-30DOI: 10.5530/jscires.12.3.061
Khairul Hafezad Abdullah
{"title":"Eco-literacy and Social Media: A Bibliometric Review","authors":"Khairul Hafezad Abdullah","doi":"10.5530/jscires.12.3.061","DOIUrl":"https://doi.org/10.5530/jscires.12.3.061","url":null,"abstract":"","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139203712","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 : 2023-11-30DOI: 10.5530/jscires.12.3.057
Pablo Jose Arana Barbier
This quantitative bibliometric research measures the efficiency of investment in R&D for the 17 more relevant countries investing in R&D through a novel indicator based on the number of scientific articles (associated with stock markets), produced for every 1% of investment in R&D in terms of GDP. The study is justified by the need to deepen the relationship between investment in R&D and economic growth, and was conducted for developed and emerging countries separately, so that the understanding of which countries or regions’ investment in R&D and its consequent scientific production has the greatest impact over the size of their economies through innovation. Our findings indicate clearly that R&D investment strongly correlates to the economy’s size of the studied countries. In addition to finding our novel indicator statistically significant with respect to economic growth through a series of multiple linear regressions and proposing economic growth not statically, but as a dynamic cumulative effect over time, this becomes more relevant for emerging countries (represented in this study by China, Brazil, India, Russia and Turkey, or BRIC + Turkey) compared to developed ones, which decants into an opportunity for scholars and particularly governments to design or restructure their R&D policies towards innovation
{"title":"The Relationship Between Scientific Production and Economic Growth Through R&D Investment: A Bibliometric Approach","authors":"Pablo Jose Arana Barbier","doi":"10.5530/jscires.12.3.057","DOIUrl":"https://doi.org/10.5530/jscires.12.3.057","url":null,"abstract":"This quantitative bibliometric research measures the efficiency of investment in R&D for the 17 more relevant countries investing in R&D through a novel indicator based on the number of scientific articles (associated with stock markets), produced for every 1% of investment in R&D in terms of GDP. The study is justified by the need to deepen the relationship between investment in R&D and economic growth, and was conducted for developed and emerging countries separately, so that the understanding of which countries or regions’ investment in R&D and its consequent scientific production has the greatest impact over the size of their economies through innovation. Our findings indicate clearly that R&D investment strongly correlates to the economy’s size of the studied countries. In addition to finding our novel indicator statistically significant with respect to economic growth through a series of multiple linear regressions and proposing economic growth not statically, but as a dynamic cumulative effect over time, this becomes more relevant for emerging countries (represented in this study by China, Brazil, India, Russia and Turkey, or BRIC + Turkey) compared to developed ones, which decants into an opportunity for scholars and particularly governments to design or restructure their R&D policies towards innovation","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139208769","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 : 2023-08-06DOI: 10.5530/jscires.12.2.034
Priti Kumari, Rajeev Kumar
Scientometrics indicators vary widely across subareas of the Computer Science (CS) discipline. Most researchers have previously analyzed scientometrics data specific to a particular subfield or a few subfields. More popular subareas lead to high scientometrics, and others have lower values. This work considers seven diversified CS subareas and six commonly used scientometrics indicators. First, we study the varying range of chosen scientometrics indicators of various subareas of the CS discipline. We explore the correlation patterns of these six indicators. Then, we consider a few combinations of these indicators and apply K -means clustering to decompose the pattern space. Correlation findings indicate that though the highly correlated indicators vary for most subfields, no single indicator can be considered equally suitable for all the subareas. The K -means clustering results show distinctive patterns across subfields, which are stable across K . The clustered subfield-specific indicators are quite distinct across subfields. This knowledge can be used as a signature for partitioning the subarea-specific indicators.
{"title":"Clustering Scientometrics of Computer Science Journals for Subarea Decomposition","authors":"Priti Kumari, Rajeev Kumar","doi":"10.5530/jscires.12.2.034","DOIUrl":"https://doi.org/10.5530/jscires.12.2.034","url":null,"abstract":"Scientometrics indicators vary widely across subareas of the Computer Science (CS) discipline. Most researchers have previously analyzed scientometrics data specific to a particular subfield or a few subfields. More popular subareas lead to high scientometrics, and others have lower values. This work considers seven diversified CS subareas and six commonly used scientometrics indicators. First, we study the varying range of chosen scientometrics indicators of various subareas of the CS discipline. We explore the correlation patterns of these six indicators. Then, we consider a few combinations of these indicators and apply K -means clustering to decompose the pattern space. Correlation findings indicate that though the highly correlated indicators vary for most subfields, no single indicator can be considered equally suitable for all the subareas. The K -means clustering results show distinctive patterns across subfields, which are stable across K . The clustered subfield-specific indicators are quite distinct across subfields. This knowledge can be used as a signature for partitioning the subarea-specific indicators.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76004603","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 : 2023-08-06DOI: 10.5530/jscires.12.2.027
Ueliton da Costa Leonidio, D. D. O. Cardoso, C. G. De Souza
University patent filings have increased worldwide over the years. However, in addition to quantity, it is important to evaluate the quality of these patents. Some studies have addressed this issue, but most of them are limited to analyzing a single or few quality indicators applied in specific areas. The literature on the subject is fragmented, so it is important to summarize this content and generate a systematized knowledge. In order to reduce this gap in the literature, this article focuses on University Patent Quality Indicators (UPQI) aiming to identify the metrics that have been used to evaluate the quality of these documents. Based on a bibliometric and systematic review, the study presents bibliometric indicators, scientific collaboration networks, keyword co-occurrence, and bibliographic coupling, as well as quality indicators found in the literature. The survey of publications was conducted on the Web of Science database. Out of a total of 760 articles, 68 were selected to present research in the field of UPQI. The results show an organized set of metrics and other information that can be used by managers, researchers and funding agencies to guide policies and decision-making that contribute to promoting technological development and partnerships with the productive sector.
近年来，世界范围内的大学专利申请量不断增加。然而，除了数量之外，评估这些专利的质量也很重要。一些研究已经解决了这个问题，但大多数研究仅限于分析应用于特定领域的单个或几个质量指标。关于该主题的文献是碎片化的，因此总结这些内容并产生系统化的知识是很重要的。为了缩小文献中的这一差距，本文将重点放在大学专利质量指标(UPQI)上，旨在确定用于评估这些文件质量的指标。在文献计量学和系统综述的基础上，研究提出了文献计量学指标、科学合作网络、关键词共现、书目耦合以及文献质量指标。对出版物的调查是在Web of Science数据库上进行的。在总共760篇文章中，有68篇被选中来介绍UPQI领域的研究。结果显示了一套有组织的指标和其他信息，管理人员、研究人员和资助机构可以使用这些指标和信息来指导有助于促进技术发展和与生产部门建立伙伴关系的政策和决策。
{"title":"Universities Patent Quality Indicators (UPQI): A Bibliometric and Systematic Review","authors":"Ueliton da Costa Leonidio, D. D. O. Cardoso, C. G. De Souza","doi":"10.5530/jscires.12.2.027","DOIUrl":"https://doi.org/10.5530/jscires.12.2.027","url":null,"abstract":"University patent filings have increased worldwide over the years. However, in addition to quantity, it is important to evaluate the quality of these patents. Some studies have addressed this issue, but most of them are limited to analyzing a single or few quality indicators applied in specific areas. The literature on the subject is fragmented, so it is important to summarize this content and generate a systematized knowledge. In order to reduce this gap in the literature, this article focuses on University Patent Quality Indicators (UPQI) aiming to identify the metrics that have been used to evaluate the quality of these documents. Based on a bibliometric and systematic review, the study presents bibliometric indicators, scientific collaboration networks, keyword co-occurrence, and bibliographic coupling, as well as quality indicators found in the literature. The survey of publications was conducted on the Web of Science database. Out of a total of 760 articles, 68 were selected to present research in the field of UPQI. The results show an organized set of metrics and other information that can be used by managers, researchers and funding agencies to guide policies and decision-making that contribute to promoting technological development and partnerships with the productive sector.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87005297","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 : 2023-08-06DOI: 10.5530/jscires.12.2.043
H. Atapour, Sonia Khalilzadeh, Rasoul Zavaraqi
In search of evidence for Wikipedia credibility, this study aims to compare and analyze articles’ references of Wikipedia and Stanford Encyclopedia of Philosophy. This research approach is quantitative and has been done using bibliometric methods and citation analysis. The statistical sample of the research were 5% of the SEP entries (84 from 1685) and their equals on Wikipedia. The samples were selected randomly and systematically, then their references were analyzed and compared. The findings showed that the frequency of SEP references was about 3.5 times more than Wikipedia. The overlap of two encyclopedia's references was 2.47% of the total references. The half-life of the SEP references was significantly longer than Wikipedia. In both encyclopedias, the main resources which were used included books, journals, and websites. Regarding language of references, most of the references of both encyclopedias was in English, and citations to other language resources in both encyclopedias were almost similar. The percentage of open access and inaccessible resources on Wikipedia was higher than the SEP, while the percentage of non-open access references in the SEP was higher than Wikipedia. Finally, a comparison of the citations received by the two encyclopedia articles’ references showed that the citations received by Wikipedia references were significantly higher than SEP. This article compares the similarity of two known encyclopedias through comparison of their entities' references. Despite the similarities in the referencing pattern of the two encyclopedias, their information content comes from different resources and comparison articles’ references of Wikipedia with SEP provide no evidence for Wikipedia's credibility.
{"title":"Comparison of Stanford Encyclopedia of Philosophy and Wikipedia Articles’ References: In Search of Evidence for Wikipedia Credibility","authors":"H. Atapour, Sonia Khalilzadeh, Rasoul Zavaraqi","doi":"10.5530/jscires.12.2.043","DOIUrl":"https://doi.org/10.5530/jscires.12.2.043","url":null,"abstract":"In search of evidence for Wikipedia credibility, this study aims to compare and analyze articles’ references of Wikipedia and Stanford Encyclopedia of Philosophy. This research approach is quantitative and has been done using bibliometric methods and citation analysis. The statistical sample of the research were 5% of the SEP entries (84 from 1685) and their equals on Wikipedia. The samples were selected randomly and systematically, then their references were analyzed and compared. The findings showed that the frequency of SEP references was about 3.5 times more than Wikipedia. The overlap of two encyclopedia's references was 2.47% of the total references. The half-life of the SEP references was significantly longer than Wikipedia. In both encyclopedias, the main resources which were used included books, journals, and websites. Regarding language of references, most of the references of both encyclopedias was in English, and citations to other language resources in both encyclopedias were almost similar. The percentage of open access and inaccessible resources on Wikipedia was higher than the SEP, while the percentage of non-open access references in the SEP was higher than Wikipedia. Finally, a comparison of the citations received by the two encyclopedia articles’ references showed that the citations received by Wikipedia references were significantly higher than SEP. This article compares the similarity of two known encyclopedias through comparison of their entities' references. Despite the similarities in the referencing pattern of the two encyclopedias, their information content comes from different resources and comparison articles’ references of Wikipedia with SEP provide no evidence for Wikipedia's credibility.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88254938","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 : 2023-08-06DOI: 10.5530/jscires.12.2.048
Yves Fassin, Ronald Rousseau
. ABSTRACT 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.
． 本文分析了文献计量学(广义)领域中最常用术语的演变。它比较了在web of science、Scopus和Dimensions这三个国际数据库中关于文献计量学、科学计量学、信息计量学、web(o)计量学、替代计量学和科学科学的出版物数量。我们发现，使用某个指标相关术语的文档的相对数量呈指数级增长。这说明了指标在科学界的重要性日益增加。虽然大多数术语单独显示出使用量的明显增加，但web(o)指标，或许还有信息指标，似乎已经达到了顶峰。文献计量学(Bibliometrics)和科学计量学(scientometrics)是最常用的术语，如今，文献计量学(Bibliometrics)的使用频率是科学计量学(scientometrics)的五倍。任何综合性文献计量学研究都应该利用相关关键词的组合来覆盖整个研究领域。
{"title":"Use of Bibliometrics-Related Terms, their Evolution, and the Growth of Metrics in Science","authors":"Yves Fassin, Ronald Rousseau","doi":"10.5530/jscires.12.2.048","DOIUrl":"https://doi.org/10.5530/jscires.12.2.048","url":null,"abstract":". ABSTRACT 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.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84956134","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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