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":"68 1","pages":""},"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":"62 1","pages":""},"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.12.2.048
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":"21 1","pages":""},"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}
Pub Date : 2023-08-06DOI: 10.5530/jscires.12.2.033
Jishant Talwar, Ashutosh Bhardwaj, Namrata Dewan Soni
Silicon carbide (SiC) is a versatile industrial material and has been in use in various spheres because of its distinctive electrical and thermal properties. Among various fields, it has contributed significantly to biosensor technologies because it is both bio and hemo-compatible. Of particular interest in this study is its potential for biomedical applications. Although about 907 SiC-based biosensor articles have been published in the past 20 years (2000–2022), not many review articles have encapsulated the advancement and uses of the SiC-based biosensor. In order to better understand the development stage, research hives, and future advancement trends of SiC-based biosensor technology, it is essential to perform a broad retrospective investigation. The present study aims to explore the potential of SiC-based biosensors and their distinct features for interdisciplinary collaborations, utilizing machine learning through big data analytics. By reviewing research in this field, the study seeks to uncover global trends, challenges, and gaps in SiC-based biosensor research, as well as identify new research areas and technologies that could advance biosensor technology. By conducting the analysis, this study provides insights into the most impactful articles and top contributors to biosensor research, including journals, authors, institutions, and countries. Additionally, the study examines the methodological approaches and research contexts employed in this field. Results suggest that one of the evolving technological paths in biosensors is the use of silicon carbide-based biosensors and medical devices, which in turn are poised to transform into the commercial sphere. The main characteristics of these emerging research grounds and technologies in biosensors are illustrated for the productive effects of research and innovation policy that led to scientific advances and technological change in society.
{"title":"Global Trends in Silicon Carbide Biosensor Research: A Bibliometric Study","authors":"Jishant Talwar, Ashutosh Bhardwaj, Namrata Dewan Soni","doi":"10.5530/jscires.12.2.033","DOIUrl":"https://doi.org/10.5530/jscires.12.2.033","url":null,"abstract":"Silicon carbide (SiC) is a versatile industrial material and has been in use in various spheres because of its distinctive electrical and thermal properties. Among various fields, it has contributed significantly to biosensor technologies because it is both bio and hemo-compatible. Of particular interest in this study is its potential for biomedical applications. Although about 907 SiC-based biosensor articles have been published in the past 20 years (2000–2022), not many review articles have encapsulated the advancement and uses of the SiC-based biosensor. In order to better understand the development stage, research hives, and future advancement trends of SiC-based biosensor technology, it is essential to perform a broad retrospective investigation. The present study aims to explore the potential of SiC-based biosensors and their distinct features for interdisciplinary collaborations, utilizing machine learning through big data analytics. By reviewing research in this field, the study seeks to uncover global trends, challenges, and gaps in SiC-based biosensor research, as well as identify new research areas and technologies that could advance biosensor technology. By conducting the analysis, this study provides insights into the most impactful articles and top contributors to biosensor research, including journals, authors, institutions, and countries. Additionally, the study examines the methodological approaches and research contexts employed in this field. Results suggest that one of the evolving technological paths in biosensors is the use of silicon carbide-based biosensors and medical devices, which in turn are poised to transform into the commercial sphere. The main characteristics of these emerging research grounds and technologies in biosensors are illustrated for the productive effects of research and innovation policy that led to scientific advances and technological change in society.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"129 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75343268","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":"13 1","pages":""},"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.12.2.044
Mitali Desai, R. Mehta, Dipti P Rana
Among available scholarly features on digitized scholarly platforms, certain features have high significance in assessing scholar's influence. If these features are identified, using them legitimately, emerging scholars can increase their influence and gain visibility in the scholars’ community. The purpose of this research is to identify and rank significant features on scholarly platforms. To select a data source, a comparative analysis of well-known scholarly platforms is performed. Based on the analysis, ResearchGate (RG) is selected. For RG, this research proposes a methodology to identify and rank significant scholarly features. The results demonstrate that for the rendered RG data, identified significant features in the order of their significance are number of citations, research items, followers, reads, recommendations, followings and projects. Significant features discovered in this research can be employed by various scholarly platforms to identify influential scholars. These scholars can be utilized in applications such as expert finding, influence ranking, recommendation systems, interdisciplinary collaborations etc. Moreover, the identified significant features will help scholars in focusing on certain aspects (features) to increase their influence legitimately.
{"title":"An Exploratory Study of Scholarly Platforms and Features to Help Emerging Scholars Gain Visibility in the Scholars’ Community","authors":"Mitali Desai, R. Mehta, Dipti P Rana","doi":"10.5530/jscires.12.2.044","DOIUrl":"https://doi.org/10.5530/jscires.12.2.044","url":null,"abstract":"Among available scholarly features on digitized scholarly platforms, certain features have high significance in assessing scholar's influence. If these features are identified, using them legitimately, emerging scholars can increase their influence and gain visibility in the scholars’ community. The purpose of this research is to identify and rank significant features on scholarly platforms. To select a data source, a comparative analysis of well-known scholarly platforms is performed. Based on the analysis, ResearchGate (RG) is selected. For RG, this research proposes a methodology to identify and rank significant scholarly features. The results demonstrate that for the rendered RG data, identified significant features in the order of their significance are number of citations, research items, followers, reads, recommendations, followings and projects. Significant features discovered in this research can be employed by various scholarly platforms to identify influential scholars. These scholars can be utilized in applications such as expert finding, influence ranking, recommendation systems, interdisciplinary collaborations etc. Moreover, the identified significant features will help scholars in focusing on certain aspects (features) to increase their influence legitimately.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"12 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78455748","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}
This article is a commentary on features and usefulness of a newly developed STI data portal, Indian Science Reports (ISR) (available at www.indianscience.net). The ISR portal is an attempt towards a systematic portal on STI data and analytics for India, both at an overall as well as at the institutional level. It can be used by a very wide audience for a variety of purposes ranging from research performance assessment to evidence-based policy formulation.
{"title":"Indian Science Reports: A Portal for Comprehensive Mapping of S&T Data and Analytics for India at an Overall and Institutional Level","authors":"Vivek Kumar Singh, Anurag Kanaujia, Prashasti Singh, Abhirup Nandy","doi":"10.5530/jscires.12.2.046","DOIUrl":"https://doi.org/10.5530/jscires.12.2.046","url":null,"abstract":"This article is a commentary on features and usefulness of a newly developed STI data portal, Indian Science Reports (ISR) (available at www.indianscience.net). The ISR portal is an attempt towards a systematic portal on STI data and analytics for India, both at an overall as well as at the institutional level. It can be used by a very wide audience for a variety of purposes ranging from research performance assessment to evidence-based policy formulation.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"74 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72450772","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.12.2.039
Mohammad Tariqur Rahman, J. V. Verhagen
Problems due to limitations of the status quo in authorship declaration across scientific fields are accumulating at an accelerating pace. Here we highlight the importance of having a mechanism to capture quantitative author contribution. That can be achieved using a range of Intellectual Activities (IAs) as recommended by International Committee for Medical Journal Editors (ICMJE), Contributor Roles Taxonomy (CRediT), or Quantitative Uniform Authorship Declaration (QUAD). Eventually, this quantitative assessment can be used to evaluate the impact of the author using the Author Performance Index (API) to avoid any superfluous credit assignment. Irrespective of the field and the online submission tool of a journal, this approach will enable the scientific community to devise a new paradigm of an objective and precise evaluation of the impact of an author in scientific communications. Not unlike climate change, adapting is inevitable, and the sooner we act the more trouble we stave off.
{"title":"Implementing Quantitative Declarations of Authorship Contribution: A Call to Action","authors":"Mohammad Tariqur Rahman, J. V. Verhagen","doi":"10.5530/jscires.12.2.039","DOIUrl":"https://doi.org/10.5530/jscires.12.2.039","url":null,"abstract":"Problems due to limitations of the status quo in authorship declaration across scientific fields are accumulating at an accelerating pace. Here we highlight the importance of having a mechanism to capture quantitative author contribution. That can be achieved using a range of Intellectual Activities (IAs) as recommended by International Committee for Medical Journal Editors (ICMJE), Contributor Roles Taxonomy (CRediT), or Quantitative Uniform Authorship Declaration (QUAD). Eventually, this quantitative assessment can be used to evaluate the impact of the author using the Author Performance Index (API) to avoid any superfluous credit assignment. Irrespective of the field and the online submission tool of a journal, this approach will enable the scientific community to devise a new paradigm of an objective and precise evaluation of the impact of an author in scientific communications. Not unlike climate change, adapting is inevitable, and the sooner we act the more trouble we stave off.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"7 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88732029","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.12.2.026
Brady Lund, Amrollah Shamsi, Arezoo Ghamgosar, N. Vasantha Raju, Hossein Dehdarirad, Mohammad Javad Mansourzadeh
Independent Researchers (IRs), namely unaffiliated or voluntary researchers, are a small yet important and distinct population of contributors to scholarly discourse. Due to their small number, IRs rarely receive attention in debates regarding scholarly publishing but the distinctiveness of the unaffiliated researchers warrants further examination. Documents were extracted from the Web of Science. Bibliometric parameters were as follows: main scientometric characteristics, citations analysis, publishing trends, geographical distributions, most productive countries, co-authorship network of countries, top funding sources, research areas, keyword co-occurrence network, top cited publications, top productive journals and gender of IRs. 3357 documents were retrieved that were individually or collaboratively authored by 3784 IRs from 1980-2021. There were 589 single-authored documents. More than 70% of documents were research articles, followed by meeting abstracts (8.66%). All documents received 52279 citations, with 19.45 average citations per document. Private Practice was the most affiliation format of IRs. Publications started to grow since 2000, with almost 40% of them published from 2017-2021. The United States published almost half of all IRs-related publications. Most of the research funding was primarily contributed by government agencies, with the United States being a major player in this regard. Also, many IRs are active in medical disciplines research, and are highly collaborative, often with multiple Co-authors. 33.5% of IRs authors were women and 66.5% were men. This understanding of IRs illustrates the importance of this group and encourages further research and support for this population of science contributors.
{"title":"Independent Researchers: A Bibliometric Analysis","authors":"Brady Lund, Amrollah Shamsi, Arezoo Ghamgosar, N. Vasantha Raju, Hossein Dehdarirad, Mohammad Javad Mansourzadeh","doi":"10.5530/jscires.12.2.026","DOIUrl":"https://doi.org/10.5530/jscires.12.2.026","url":null,"abstract":"Independent Researchers (IRs), namely unaffiliated or voluntary researchers, are a small yet important and distinct population of contributors to scholarly discourse. Due to their small number, IRs rarely receive attention in debates regarding scholarly publishing but the distinctiveness of the unaffiliated researchers warrants further examination. Documents were extracted from the Web of Science. Bibliometric parameters were as follows: main scientometric characteristics, citations analysis, publishing trends, geographical distributions, most productive countries, co-authorship network of countries, top funding sources, research areas, keyword co-occurrence network, top cited publications, top productive journals and gender of IRs. 3357 documents were retrieved that were individually or collaboratively authored by 3784 IRs from 1980-2021. There were 589 single-authored documents. More than 70% of documents were research articles, followed by meeting abstracts (8.66%). All documents received 52279 citations, with 19.45 average citations per document. Private Practice was the most affiliation format of IRs. Publications started to grow since 2000, with almost 40% of them published from 2017-2021. The United States published almost half of all IRs-related publications. Most of the research funding was primarily contributed by government agencies, with the United States being a major player in this regard. Also, many IRs are active in medical disciplines research, and are highly collaborative, often with multiple Co-authors. 33.5% of IRs authors were women and 66.5% were men. This understanding of IRs illustrates the importance of this group and encourages further research and support for this population of science contributors.","PeriodicalId":43282,"journal":{"name":"Journal of Scientometric Research","volume":"51 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2023-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90808576","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.12.2.042
A. Müngen
This study investigates the variations in lexical richness within English language theses across diverse disciplines, focusing on areas where researchers exhibit higher degrees of lexical richness and the evolution of vocabulary usage over time. By analyzing these variations, the research aims to provide insights into the effective use of lexical richness in academic writing and contribute to the development of more engaging and comprehensible scholarly publications. A total of 320 theses were randomly selected from the Turkey National Thesis Center and classified according to their scientific discipline. Using natural language processing techniques, unique word count, word diversity, and other metrics were analyzed. Results reveal that social sciences tend to exhibit higher lexical richness compared to natural sciences, and no significant difference was observed in word richness between social and natural sciences disciplines. These findings contribute to the understanding of lexical richness in academic writing and highlight the importance of achieving a balance between lexical richness and readability.
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