Pub Date : 2023-01-01DOI: 10.47974/cjsim-2022-0063
Humberta Karinne Da Conceição Santos Silva, L. Vasconcellos
This article examines, with bibliometrics, the publication on bias in organizations’ personnel selection processes, whether they use automated decision-making systems or human-made decisions. While human bias is dynamic, restricted, mutate, and easier to determine the source; algorithmic bias is large-scale, static, and unpredictable. Despite the apparent discrepancy, there is a symbiotic relationship between those two, but somehow only one of them is getting any attention regarding the consequences of fairness on personnel selection and how this influences organizational diversity. So, looking for a better understanding of organizational behaviour, we conduct a bibliometric review to mappings the relations of these two. Here we reviewed 55 articles from the Web of Science Core Collection, from the earliest research published in 1979 to 2021. Only papers of the document type “article” was considered. The tool used for bibliometric data analysis were bibliometrix packages from the RStudio system version 3.6.3. According to our review, the number of studies on the subject is still tiny, and most of them were conducted under controlled conditions without considering the error agent of an organizational environment such as time, organizational culture, and the emotions of the recruiter; this makes it impossible to develop practices to avoid discrimination in these spaces. Concerning the theme, studies on human bias are the most common, with a focus on gender bias, and have recently adopted diversity. Hardly studies on algorithm decision-making consider the process’s fairness as a topic for investigation. However, neither study demonstrates a correlation or systematic approach between them. More interdisciplinary and empirical research should be the focus of future studies.
本文通过文献计量学研究了组织人员选择过程中的偏见，无论他们是使用自动决策系统还是人为决策。虽然人类的偏见是动态的、受限制的、变异的，而且更容易确定来源;算法偏差是大规模的、静态的、不可预测的。尽管存在明显的差异，但这两者之间存在共生关系，但不知何故，只有其中一个在人员选择的公平性后果以及这如何影响组织多样性方面得到了关注。因此，为了更好地理解组织行为，我们进行了文献计量审查，以映射这两者的关系。在这里，我们回顾了来自Web of Science核心合集的55篇文章，从1979年最早发表的研究到2021年。只审议文件类型为“文章”的文件。用于文献计量数据分析的工具是来自RStudio系统版本3.6.3的bibliometrix包。根据我们的回顾，关于这一主题的研究数量仍然很少，而且大多数研究都是在受控条件下进行的，没有考虑组织环境的误差因素，如时间、组织文化和招聘人员的情绪;这使得在这些空间中不可能制定避免歧视的做法。关于这一主题，对人类偏见的研究最为常见，主要集中在性别偏见上，并且最近采取了多样性的研究。在算法决策研究中，很少把过程的公平性作为一个研究课题。然而，这两项研究都没有证明它们之间存在相关性或系统方法。更多的跨学科和实证研究应成为未来研究的重点。
{"title":"Human and algorithmic decision-making in the personnel selection process: A comparative bibliometric on bias","authors":"Humberta Karinne Da Conceição Santos Silva, L. Vasconcellos","doi":"10.47974/cjsim-2022-0063","DOIUrl":"https://doi.org/10.47974/cjsim-2022-0063","url":null,"abstract":"This article examines, with bibliometrics, the publication on bias in organizations’ personnel selection processes, whether they use automated decision-making systems or human-made decisions. While human bias is dynamic, restricted, mutate, and easier to determine the source; algorithmic bias is large-scale, static, and unpredictable. Despite the apparent discrepancy, there is a symbiotic relationship between those two, but somehow only one of them is getting any attention regarding the consequences of fairness on personnel selection and how this influences organizational diversity. So, looking for a better understanding of organizational behaviour, we conduct a bibliometric review to mappings the relations of these two. Here we reviewed 55 articles from the Web of Science Core Collection, from the earliest research published in 1979 to 2021. Only papers of the document type “article” was considered. The tool used for bibliometric data analysis were bibliometrix packages from the RStudio system version 3.6.3. According to our review, the number of studies on the subject is still tiny, and most of them were conducted under controlled conditions without considering the error agent of an organizational environment such as time, organizational culture, and the emotions of the recruiter; this makes it impossible to develop practices to avoid discrimination in these spaces. Concerning the theme, studies on human bias are the most common, with a focus on gender bias, and have recently adopted diversity. Hardly studies on algorithm decision-making consider the process’s fairness as a topic for investigation. However, neither study demonstrates a correlation or systematic approach between them. More interdisciplinary and empirical research should be the focus of future studies.","PeriodicalId":10501,"journal":{"name":"COLLNET Journal of Scientometrics and Information Management","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70464231","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 : 2023-01-01DOI: 10.47974/cjsim-2021-0103
Bisma Bashir, Fayaz Ahmad Loan
Purpose: The purpose of the study is to conduct a scientometric analysis of expert systems literature indexed in the Science Citation Index Expanded (SCIE) of the Web of Science database for a period of ten years (2011-2020). Design/Methodology: The study collected data from the Science Citation Index Expanded (SCIE) of the Web of Science (WoS) database from 2011-2020. The synonymous, broader and related terms of Expert Systems were selected from the Dewey Decimal Classification Scheme and Sears List of Subject Headings. A string of these terms was employed to retrieve data in the advanced search mode of the database. The harvested data was analyzed using scientometric techniques. Besides, the Microsoft Excel and VOSviewer software were used to represent and map the research productivity on expert systems. Findings: The results indicated inconsistent fluctuations in the annual number of publications from 396 in 2011 to 463 in 2020 and a decline in the number of citations from 8344 in 2011 to 520 in 2020. Further, it is divulged that China, the USA, and Spain are the three top countries contributing to expert system research published 16.36%, 14.96%, and 8.95% of literature respectively. While analysing institutional performance, the results revealed that most of the institutions are from China (6), followed by Iran (4), Spain (3) and India (2) /Malaysia (2) respectively. Further, by clustering the network map for keywords co-occurrence, it was found that expert systems, fuzzy logic, knowledge-based systems, machine learning, and artificial intelligence are the most common keywords and hence the hot topics of research in the area. Practical implications: The findings of the study may help researchers, information scientists and technologists to identify the research progress in the field of expert systems. Besides, it will help librarians to know the hot topics of research, prominent publications and prolific authors in expert systems. This will be helpful in the collection development of expert systems and artificial intelligence in libraries and information centres. Research limitations: The database studied for the work does not represent the total literary output available on expert systems as data in other databases like Scopus, Compendex, IEEE Xplore, arXiv, etc. haven’t been harvested. Originality/Value: The study is based on current literature on expert systems and will highlight new research trends in the said field.
目的:本研究的目的是对Web of Science数据库SCIE收录的专家系统文献进行为期十年(2011-2020)的科学计量学分析。设计/方法:本研究收集了Web of Science (WoS)数据库2011-2020年的科学引文索引扩展(SCIE)数据。专家系统的同义，更广泛和相关的术语是从杜威十进分类方案和西尔斯主题标题列表中选择的。使用这些术语的字符串在数据库的高级搜索模式中检索数据。收集的数据使用科学计量学技术进行分析。此外，还利用Microsoft Excel和VOSviewer软件对专家系统的研究生产力进行了表示和映射。研究发现:论文年发表数从2011年的396篇波动到2020年的463篇，引用数从2011年的8344篇下降到2020年的520篇。此外，据透露，中国、美国和西班牙是对专家系统研究贡献最大的三个国家，分别发表了16.36%、14.96%和8.95%的文献。在分析机构绩效时，结果显示，大多数机构来自中国(6所)，其次是伊朗(4所)、西班牙(3所)和印度(2所)/马来西亚(2所)。此外，通过对关键词共现的网络图进行聚类，发现专家系统、模糊逻辑、知识系统、机器学习和人工智能是最常见的关键词，因此是该领域的研究热点。实践意义:本研究的发现可以帮助研究人员、信息科学家和技术人员识别专家系统领域的研究进展。此外，它还可以帮助图书馆员了解专家系统的研究热点、知名出版物和高产作者。这将有助于图书馆和信息中心的专家系统和人工智能的收藏发展。研究限制:研究的数据库并不代表专家系统上可用的全部文献输出，因为其他数据库(如Scopus, Compendex, IEEE Xplore, arXiv等)中的数据尚未收获。原创性/价值:该研究基于当前专家系统的文献，并将突出该领域的新研究趋势。
{"title":"Mapping global research on expert systems","authors":"Bisma Bashir, Fayaz Ahmad Loan","doi":"10.47974/cjsim-2021-0103","DOIUrl":"https://doi.org/10.47974/cjsim-2021-0103","url":null,"abstract":"Purpose: The purpose of the study is to conduct a scientometric analysis of expert systems literature indexed in the Science Citation Index Expanded (SCIE) of the Web of Science database for a period of ten years (2011-2020). Design/Methodology: The study collected data from the Science Citation Index Expanded (SCIE) of the Web of Science (WoS) database from 2011-2020. The synonymous, broader and related terms of Expert Systems were selected from the Dewey Decimal Classification Scheme and Sears List of Subject Headings. A string of these terms was employed to retrieve data in the advanced search mode of the database. The harvested data was analyzed using scientometric techniques. Besides, the Microsoft Excel and VOSviewer software were used to represent and map the research productivity on expert systems. Findings: The results indicated inconsistent fluctuations in the annual number of publications from 396 in 2011 to 463 in 2020 and a decline in the number of citations from 8344 in 2011 to 520 in 2020. Further, it is divulged that China, the USA, and Spain are the three top countries contributing to expert system research published 16.36%, 14.96%, and 8.95% of literature respectively. While analysing institutional performance, the results revealed that most of the institutions are from China (6), followed by Iran (4), Spain (3) and India (2) /Malaysia (2) respectively. Further, by clustering the network map for keywords co-occurrence, it was found that expert systems, fuzzy logic, knowledge-based systems, machine learning, and artificial intelligence are the most common keywords and hence the hot topics of research in the area. Practical implications: The findings of the study may help researchers, information scientists and technologists to identify the research progress in the field of expert systems. Besides, it will help librarians to know the hot topics of research, prominent publications and prolific authors in expert systems. This will be helpful in the collection development of expert systems and artificial intelligence in libraries and information centres. Research limitations: The database studied for the work does not represent the total literary output available on expert systems as data in other databases like Scopus, Compendex, IEEE Xplore, arXiv, etc. haven’t been harvested. Originality/Value: The study is based on current literature on expert systems and will highlight new research trends in the said field.","PeriodicalId":10501,"journal":{"name":"COLLNET Journal of Scientometrics and Information Management","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70464066","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 : 2023-01-01DOI: 10.47974/cjsim-2022-0023
B. Gupta, S. Dhawan, G. M. Mamdapur
The study provides a quantitative and qualitative description of global research in “Natural Language Processing” ( NLP) using bibliometric methods. The analysis is based on publications data sourced from Scopus database for the period 2001-2020. The purpose of the study is to understand the status of NLP research at the global, national, institutional, and author level. The study highlights the productivity and performance of NLP research on a series of metrics as well as provides a visual view of collaborative network relationship between authors, research institutions, and leading countries using standard software tools. In addition, the study identified the leading players in NLP research such as key countries, institutions, authors, and areas of research. According to the study, the USA leads in global publications output as well as it leads in terms of relative citation index.
{"title":"Research trends in the field of natural language processing : A scientometric study based on global publications during 2001-2020","authors":"B. Gupta, S. Dhawan, G. M. Mamdapur","doi":"10.47974/cjsim-2022-0023","DOIUrl":"https://doi.org/10.47974/cjsim-2022-0023","url":null,"abstract":"The study provides a quantitative and qualitative description of global research in “Natural Language Processing” ( NLP) using bibliometric methods. The analysis is based on publications data sourced from Scopus database for the period 2001-2020. The purpose of the study is to understand the status of NLP research at the global, national, institutional, and author level. The study highlights the productivity and performance of NLP research on a series of metrics as well as provides a visual view of collaborative network relationship between authors, research institutions, and leading countries using standard software tools. In addition, the study identified the leading players in NLP research such as key countries, institutions, authors, and areas of research. According to the study, the USA leads in global publications output as well as it leads in terms of relative citation index.","PeriodicalId":10501,"journal":{"name":"COLLNET Journal of Scientometrics and Information Management","volume":"38 4 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70464186","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 : 2023-01-01DOI: 10.47974/cjsim-2022-0074
L. Parabhoi, Damodar Parabhoi, Ramani Ranjan Sahu, M. Verma, R. S. Dewey
Altmetrics indicators are useful for assessing the impact of research and have been increasingly used alongside traditional citations in recent years. Mendeley provides readership statistics which give an early indicator of the impact of research outputs. This study aimed to investigate how Mendeley early readership indicator was associated with later citations across nine selected library and information science (LIS) journals. This study examined bibliographic data of 9 LIS journals extracted from the Scopus database over a 17 months period from June 2019 to November 2020. Data were extracted using Webometric Analyst. Spearman’s rank correlation coefficient was used to characterize the relationship between these two variables. The number of readers per paper, and of each journal are described using mean, standard deviation, frequency, and geometric mean. Readership growth was increased in all selected journals, but citation growth was unstable in most of the journals. Early readership statistics positively correlated with early citation analysis in all journals except the Journal of Educational Media and Library Science, which had a weaker positive correlation. The correlation between early readership and later citation numbers varied, with some journals being moderately positive and some weakly positive.
{"title":"The association between Mendeley early readership and later citations in library and information science journals","authors":"L. Parabhoi, Damodar Parabhoi, Ramani Ranjan Sahu, M. Verma, R. S. Dewey","doi":"10.47974/cjsim-2022-0074","DOIUrl":"https://doi.org/10.47974/cjsim-2022-0074","url":null,"abstract":"Altmetrics indicators are useful for assessing the impact of research and have been increasingly used alongside traditional citations in recent years. Mendeley provides readership statistics which give an early indicator of the impact of research outputs. This study aimed to investigate how Mendeley early readership indicator was associated with later citations across nine selected library and information science (LIS) journals. This study examined bibliographic data of 9 LIS journals extracted from the Scopus database over a 17 months period from June 2019 to November 2020. Data were extracted using Webometric Analyst. Spearman’s rank correlation coefficient was used to characterize the relationship between these two variables. The number of readers per paper, and of each journal are described using mean, standard deviation, frequency, and geometric mean. Readership growth was increased in all selected journals, but citation growth was unstable in most of the journals. Early readership statistics positively correlated with early citation analysis in all journals except the Journal of Educational Media and Library Science, which had a weaker positive correlation. The correlation between early readership and later citation numbers varied, with some journals being moderately positive and some weakly positive.","PeriodicalId":10501,"journal":{"name":"COLLNET Journal of Scientometrics and Information Management","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70464487","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 : 2023-01-01DOI: 10.47974/cjsim-2020-0097
Jie Sun, Bao-Zhong Yuan
Based on the ESI database, this study analyzed 612 top papers in the subject category of soil science from 2009 to 2019, which includes 608 highly cited papers and 17 hot papers, of which 4 are only hot papers and other 13 papers are both hot papers and highly cited papers. Top 5 core journals with higher impact factor ranked as Soil Biology Biochemistry, Geoderma, Plant and Soil, Catena, Soil Tillage Research. Top 5 countries and regions were Peoples R China, USA, Germany, Australia, France. The study also analysed that top 5 organizations were Chinese Acad Sci, Univ Western Australia, Univ Chinese Acad Sci, INRA, Nanjing Agr Univ. The analysis of all keywords showed that the research was separated in clusters. Therefore, authors can choose their ideal journal with a high impact factor to publish papers in the English language related to this research field.
{"title":"Mapping of top papers in the subject category of Soil Science","authors":"Jie Sun, Bao-Zhong Yuan","doi":"10.47974/cjsim-2020-0097","DOIUrl":"https://doi.org/10.47974/cjsim-2020-0097","url":null,"abstract":"Based on the ESI database, this study analyzed 612 top papers in the subject category of soil science from 2009 to 2019, which includes 608 highly cited papers and 17 hot papers, of which 4 are only hot papers and other 13 papers are both hot papers and highly cited papers. Top 5 core journals with higher impact factor ranked as Soil Biology Biochemistry, Geoderma, Plant and Soil, Catena, Soil Tillage Research. Top 5 countries and regions were Peoples R China, USA, Germany, Australia, France. The study also analysed that top 5 organizations were Chinese Acad Sci, Univ Western Australia, Univ Chinese Acad Sci, INRA, Nanjing Agr Univ. The analysis of all keywords showed that the research was separated in clusters. Therefore, authors can choose their ideal journal with a high impact factor to publish papers in the English language related to this research field.","PeriodicalId":10501,"journal":{"name":"COLLNET Journal of Scientometrics and Information Management","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70463997","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 : 2023-01-01DOI: 10.47974/cjsim-2022-0067
Abinash Panda, B. Maharana, S. Sahu
Core journals in any subject go through evolution processes before being accepted worldwide. The study of the journal’s evolution with its long publication history gives insight into distinct characteristics acquired over time. This study explores the dynamics in scientometrics indicators of three distinct Physics journals with the same scope but published from different regions and impact factors. The result shows each journal has its discrete contributors, but the host or home country contributes more than 50%. In short or medium duration (decadal), the increase in authorship per article differs from journal to journal. Still, the change is approximately the same over a longer duration (1990-2019) (46.38% to 48.5%). A journal with linear authorship growth only correlates significantly with its impact factor (r = 0.877). These journals also show an increase in international coauthored publications, but the increase mostly depends on the host country’s collaborations. More than 80% of associations are between two countries. The findings establish that irrespective of Physics’s global use and implications, the researchers tend to publish in familiar journals from their region regardless of impact factors. The journals with higher impact factors publish more transnational articles.
{"title":"Dynamics of Scientometrics Indicators in three distinct Physics Journals with long publication history","authors":"Abinash Panda, B. Maharana, S. Sahu","doi":"10.47974/cjsim-2022-0067","DOIUrl":"https://doi.org/10.47974/cjsim-2022-0067","url":null,"abstract":"Core journals in any subject go through evolution processes before being accepted worldwide. The study of the journal’s evolution with its long publication history gives insight into distinct characteristics acquired over time. This study explores the dynamics in scientometrics indicators of three distinct Physics journals with the same scope but published from different regions and impact factors. The result shows each journal has its discrete contributors, but the host or home country contributes more than 50%. In short or medium duration (decadal), the increase in authorship per article differs from journal to journal. Still, the change is approximately the same over a longer duration (1990-2019) (46.38% to 48.5%). A journal with linear authorship growth only correlates significantly with its impact factor (r = 0.877). These journals also show an increase in international coauthored publications, but the increase mostly depends on the host country’s collaborations. More than 80% of associations are between two countries. The findings establish that irrespective of Physics’s global use and implications, the researchers tend to publish in familiar journals from their region regardless of impact factors. The journals with higher impact factors publish more transnational articles.","PeriodicalId":10501,"journal":{"name":"COLLNET Journal of Scientometrics and Information Management","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70464375","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 : 2023-01-01DOI: 10.47974/cjsim-2022-0043
Saloni Chaudhary, Bhaskar Mukherjee
Using more than one lakh publication records from the Web of Science database, we tried to identify the scientific activity (publications, collaborations and citations), sectors of collaboration (University- Industry-Government), & subjects of collaboration in the top 10 NIRF ranked engineering institutes and universities in India. The study indicated that collaboration in different types of academic institutions has steadily increased from 2011 to 2020. Greater growth has been observed in domestic collaboration than foreign collaboration. The international collaboration network tends to be very dense with more advantageous countries. Although, international collaboration resulting in more citations, the fractional impact strength of domestic publications is better than foreign. The impact factor of the journal was observed to be a better predictor than the number of authors per article. University-University sector – mainly different departments of the same institute emerge as the predominant form of domestic collaborative research. While assessing the disciplinary output of the top 10 institutions by establishing a subject framework based on the Frascati Manual and Essential Science Indicator of Clarivate, it was observed that Civil, Mechanical & Electrical Engineering; Chemical, Material & Environmental Engineering; Chemical Sciences, and Theoretical aspects of Physics were the major fields amongst science disciplines with overall 52% of domestic and 48% of foreign collaboration.
利用来自Web of Science数据库的10多万条出版记录，我们试图确定印度排名前10位的工程学院和大学的科学活动(出版物、合作和引用)、合作部门(大学-工业-政府)和合作主题。研究表明，从2011年到2020年，不同类型学术机构的合作稳步增长。国内合作比国外合作增长更快。国际合作网络趋于密集，优势国家较多。虽然国际合作导致了更多的引用，但国内出版物的分数影响强度优于国外。研究发现，期刊的影响因子比每篇文章的作者数量更能预测结果。大学-大学部门-主要是同一研究所的不同部门-成为国内合作研究的主要形式。在以Frascati手册和Clarivate基本科学指标为基础，建立学科框架，对排名前10位的院校进行学科产出评估时，发现土木、机械与电气工程;化学、材料与环境工程;化学科学和物理理论方面是科学学科中的主要领域，占国内合作的52%，占国外合作的48%。
{"title":"Scientific activities, and extent of collaborative efforts in the top academic institutions of India : A scientometric study using Web of Science data","authors":"Saloni Chaudhary, Bhaskar Mukherjee","doi":"10.47974/cjsim-2022-0043","DOIUrl":"https://doi.org/10.47974/cjsim-2022-0043","url":null,"abstract":"Using more than one lakh publication records from the Web of Science database, we tried to identify the scientific activity (publications, collaborations and citations), sectors of collaboration (University- Industry-Government), & subjects of collaboration in the top 10 NIRF ranked engineering institutes and universities in India. The study indicated that collaboration in different types of academic institutions has steadily increased from 2011 to 2020. Greater growth has been observed in domestic collaboration than foreign collaboration. The international collaboration network tends to be very dense with more advantageous countries. Although, international collaboration resulting in more citations, the fractional impact strength of domestic publications is better than foreign. The impact factor of the journal was observed to be a better predictor than the number of authors per article. University-University sector – mainly different departments of the same institute emerge as the predominant form of domestic collaborative research. While assessing the disciplinary output of the top 10 institutions by establishing a subject framework based on the Frascati Manual and Essential Science Indicator of Clarivate, it was observed that Civil, Mechanical & Electrical Engineering; Chemical, Material & Environmental Engineering; Chemical Sciences, and Theoretical aspects of Physics were the major fields amongst science disciplines with overall 52% of domestic and 48% of foreign collaboration.","PeriodicalId":10501,"journal":{"name":"COLLNET Journal of Scientometrics and Information Management","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70464389","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 : 2023-01-01DOI: 10.47974/cjsim-2022-0050
Shradha Deshmukh, Preeti Mulay
The composition tunable and special size electronic feature of quantum dots makes promising feature of quantum dots and promising number of new technologies and applications. Understanding the research patterns and opportunities in the field of quantum dots, gives birth to advanced technologies. Nowadays it is essential to examine the transition in artificial atoms that is quantum dots to the next generation evolution and biosafety. The paper gives the analysis of scientific publications in the field of quantum dots. The quantitative and qualitative analysis of the research publication of quantum dots in quantum computing revealed the emerging sub-field and future development trends. The paper focuses on the relevant publications from 1986 to early mid of 2022, using Scopus and Web of Science research database. Using the popular search keywords, the analysis not only focuses on trends of the quantum dots in quantum computing but also points out future directions for the researchers.
量子点的组成可调和特殊尺寸的电子特性，使得量子点具有广阔的应用前景和大量的新技术。了解量子点领域的研究模式和机会，可以催生先进的技术。目前，研究人工原子即量子点向下一代进化和生物安全的过渡是十分必要的。本文对量子点领域的科学出版物进行了分析。对量子点在量子计算中的研究成果进行了定量和定性分析，揭示了量子点在量子计算中的新兴子领域和未来发展趋势。利用Scopus和Web of Science研究数据库，以1986年至2022年中期的相关论文为研究对象。利用热门搜索关键词，分析量子点在量子计算中的发展趋势，并为研究人员指出未来的发展方向。
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Pub Date : 2023-01-01DOI: 10.47974/cjsim-2022-0047
Shrikrishna Kolhar, Jayant Jagtap, A. Tiwari
Plant phenotyping involves the measurement of observable traits of plants. Plant traits like leaf area, leaf count, leaf surface temperature, chlorophyll content, plant growth rate, emergence time of leaves, and reproductive organs depend on the interaction of its genotype with the environment. Plant phenotyping serves to analyze biotic and abiotic stresses on plants, select crop varieties resilient to the surrounding environment, and improve crop yield. Recent advancements in imaging technologies help expedite the growth of automatic, non-invasive, and efficient plant phenotyping systems. These plant phenotyping systems involve using different imaging techniques like visible imaging, hyperspectral imaging, chlorophyll fluorescence imaging (CFIM), thermal imaging to record, monitor, and analyze plant phenotypes using images. In the last few years, researchers have been working on developing image processing, computer vision, machine learning, and deep learning approaches for the accurate and precise analysis of plant images. Therefore, this paper reviews and presents insights about the research reported through patents in the area of automatic plant phenotyping. This review report uses patent databases like Espacenet, Lens, and Google Patents to search, review and analyze patent documents. The paper presents a patentometric analysis of all 67 patent documents available till date focusing on automatic image-based plant phenotyping. The review provides a summary and analysis of outstanding patents in terms of qualitative and quantitative patent indices. This article provides a comprehensive global patent study to aid researchers and scientists develop more efficient plant phenotyping algorithms, devices, and systems.
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Pub Date : 2023-01-01DOI: 10.47974/cjsim-2022-0029
O. Tantengco, Y. Ho
Background: Analyzing classic articles or research papers that received total citations of 1000 or more has helped study the evolution of research trends and identify research gaps and future directions in a particular field. This study used a bibliometric approach to analyzing classic articles in cervical cancer research. Method: Classic articles in cervical cancer research with 1,000 or more citations from the Web of Science Core Collection from publication to the end of 2020 were analyzed using bibliometric analysis. These methods determine the document types, most productive countries, institutions, and journals for classic articles in cervical cancer research. Moreover, it also determined their research impact through the years by analyzing their citation histories. Result: We documented 46 classic cervical cancer research papers published in the Web of Science from 1983 until 2019. The CA-A Cancer Journal for Clinicians and the New England Journal of Medicine were the most productive journals that published seven classic cervical cancer articles. The USA was the most productive country, with 28 classic cervical cancer articles. The International Agency for Research on Cancer in France and the American Cancer Society in the USA were the most effective and impactful institutions in cervical cancer research. Citation histories revealed that the most important and cited papers in recent years were cancer statistics that report incidence and mortality from cervical cancer worldwide. The most impactful studies include articles on HPV as a necessary cause of cervical cancer, the discovery and development of HPV vaccines to prevent cervical cancer, and the development of chemotherapy, radiotherapy, and surgical treatment for cervical cancer. Conclusion: This study showed cervical cancer research’s most productive countries, institutions, and journals. It also demonstrated the citation history of these classic articles, which showed influential studies still relevant to cervical cancer research until recently.
背景:分析总被引次数在1000次或以上的经典文章或研究论文有助于研究研究趋势的演变，并确定特定领域的研究差距和未来方向。本研究采用文献计量学方法分析宫颈癌研究的经典文献。方法:采用文献计量学分析方法，对Web of Science核心馆藏自发表至2020年底被引频次在1000次及以上的宫颈癌研究经典文章进行分析。这些方法决定了文献类型、最多产的国家、机构和期刊在宫颈癌研究中的经典文章。此外，还通过分析他们的引文历史来确定他们多年来的研究影响力。结果:我们记录了从1983年到2019年发表在Web of Science上的46篇经典宫颈癌研究论文。《CA-A临床医生癌症杂志》和《新英格兰医学杂志》是发表七篇经典宫颈癌文章最多的期刊。美国是最多产的国家，有28篇经典宫颈癌文章。法国的国际癌症研究机构和美国的美国癌症协会是宫颈癌研究中最有效和最有影响力的机构。引用历史表明，近年来最重要和被引用的论文是报告全球宫颈癌发病率和死亡率的癌症统计。最具影响力的研究包括关于HPV是宫颈癌的必要原因的文章，HPV疫苗的发现和发展，以预防宫颈癌，以及宫颈癌的化疗，放疗和手术治疗的发展。结论:本研究显示了宫颈癌研究最高产的国家、机构和期刊。并展示了这些经典文章的引用历史，其中显示了直到最近仍与宫颈癌研究相关的有影响力的研究。
{"title":"Classic articles in cervical cancer research : A bibliometric analysis","authors":"O. Tantengco, Y. Ho","doi":"10.47974/cjsim-2022-0029","DOIUrl":"https://doi.org/10.47974/cjsim-2022-0029","url":null,"abstract":"Background: Analyzing classic articles or research papers that received total citations of 1000 or more has helped study the evolution of research trends and identify research gaps and future directions in a particular field. This study used a bibliometric approach to analyzing classic articles in cervical cancer research. Method: Classic articles in cervical cancer research with 1,000 or more citations from the Web of Science Core Collection from publication to the end of 2020 were analyzed using bibliometric analysis. These methods determine the document types, most productive countries, institutions, and journals for classic articles in cervical cancer research. Moreover, it also determined their research impact through the years by analyzing their citation histories. Result: We documented 46 classic cervical cancer research papers published in the Web of Science from 1983 until 2019. The CA-A Cancer Journal for Clinicians and the New England Journal of Medicine were the most productive journals that published seven classic cervical cancer articles. The USA was the most productive country, with 28 classic cervical cancer articles. The International Agency for Research on Cancer in France and the American Cancer Society in the USA were the most effective and impactful institutions in cervical cancer research. Citation histories revealed that the most important and cited papers in recent years were cancer statistics that report incidence and mortality from cervical cancer worldwide. The most impactful studies include articles on HPV as a necessary cause of cervical cancer, the discovery and development of HPV vaccines to prevent cervical cancer, and the development of chemotherapy, radiotherapy, and surgical treatment for cervical cancer. Conclusion: This study showed cervical cancer research’s most productive countries, institutions, and journals. It also demonstrated the citation history of these classic articles, which showed influential studies still relevant to cervical cancer research until recently.","PeriodicalId":10501,"journal":{"name":"COLLNET Journal of Scientometrics and Information Management","volume":"1 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70464214","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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