Pub Date : 2021-07-03DOI: 10.1080/09737766.2021.1958659
Shahab Mosallaie, M. Rad, Andrea Schiffauerova, Ashkan Ebadi
The rapid growth of healthcare data in recent years calls for more advanced and efficient analytic techniques. Artificial intelligence facilitates finding insightful patterns in massive high-dimensional data. Considering the latest movements towards using machine learning and deep learning techniques in the medical domain, in this study, we focused on the publications in which researchers employed artificial intelligence techniques for cancer diagnosis and treatment. Using dynamic topic modeling and natural language processing techniques, we analyzed the contents and trends of more than 12,000 scientific publications within the period of 2000 to 2018, extracted from two different sources, i.e., Elsevier’s Scopus and PubMed. While drawing the landscape of cancer research, our results also shed light on the evolution of artificial intelligence techniques and algorithms used for cancer diagnosis and treatment. Our findings confirm that modern computer science algorithms are being widely applied to extract patterns from large-scale medical images to cure different types of cancer with a special focus on deep learning techniques in recent years.
{"title":"Discovering the evolution of artificial intelligence in cancer research using dynamic topic modeling","authors":"Shahab Mosallaie, M. Rad, Andrea Schiffauerova, Ashkan Ebadi","doi":"10.1080/09737766.2021.1958659","DOIUrl":"https://doi.org/10.1080/09737766.2021.1958659","url":null,"abstract":"The rapid growth of healthcare data in recent years calls for more advanced and efficient analytic techniques. Artificial intelligence facilitates finding insightful patterns in massive high-dimensional data. Considering the latest movements towards using machine learning and deep learning techniques in the medical domain, in this study, we focused on the publications in which researchers employed artificial intelligence techniques for cancer diagnosis and treatment. Using dynamic topic modeling and natural language processing techniques, we analyzed the contents and trends of more than 12,000 scientific publications within the period of 2000 to 2018, extracted from two different sources, i.e., Elsevier’s Scopus and PubMed. While drawing the landscape of cancer research, our results also shed light on the evolution of artificial intelligence techniques and algorithms used for cancer diagnosis and treatment. Our findings confirm that modern computer science algorithms are being widely applied to extract patterns from large-scale medical images to cure different types of cancer with a special focus on deep learning techniques in recent years.","PeriodicalId":10501,"journal":{"name":"COLLNET Journal of Scientometrics and Information Management","volume":"15 1","pages":"225 - 240"},"PeriodicalIF":1.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47651683","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 : 2021-07-03DOI: 10.1080/09737766.2021.1977094
Jânio Rodrigo de Jesus Santos, Carlos Augusto Francisco de Jesus, Cláudio Damasceno Pinto
The objective is to map the scientific publications of research involving stem cells associated with Chagas disease. We used bibliometric and social network analysis techniques to analyze scientific data collected in the Web of Science. Most of the articles were published in 2014 and 2015. The organizations and authors with the largest number of publications and research collaborations are located in america, specifically in Brazil and the United States, which are responsible for 62% of all publications. FIOCRUZ, UFRJ, and Hospital São Rafael together account for approximately 55% of the studies related to stem cells associated with Chagas disease. Most of the studies focus on developing new strategies for treating Chagas disease using stem cells. This suggests that the research agenda in this area is still under development, highlighting the importance of continuing to pursue existing research avenues and expanding the range of strategies for the treatment of the disease.
目标是绘制涉及与恰加斯病有关的干细胞研究的科学出版物。我们使用文献计量学和社会网络分析技术来分析在Web of Science中收集的科学数据。大部分文章发表于2014年和2015年。出版和研究合作数量最多的组织和作者位于美国，特别是巴西和美国，占所有出版物的62%。FIOCRUZ, UFRJ和Hospital sso Rafael总共占了大约55%的与恰加斯病相关的干细胞研究。大多数研究集中于开发利用干细胞治疗恰加斯病的新策略。这表明这一领域的研究议程仍在制定中，突出了继续探索现有研究途径和扩大治疗该疾病战略范围的重要性。
{"title":"Scientific mapping of stem cells associated with Chagas disease : A bibliometric analysis","authors":"Jânio Rodrigo de Jesus Santos, Carlos Augusto Francisco de Jesus, Cláudio Damasceno Pinto","doi":"10.1080/09737766.2021.1977094","DOIUrl":"https://doi.org/10.1080/09737766.2021.1977094","url":null,"abstract":"The objective is to map the scientific publications of research involving stem cells associated with Chagas disease. We used bibliometric and social network analysis techniques to analyze scientific data collected in the Web of Science. Most of the articles were published in 2014 and 2015. The organizations and authors with the largest number of publications and research collaborations are located in america, specifically in Brazil and the United States, which are responsible for 62% of all publications. FIOCRUZ, UFRJ, and Hospital São Rafael together account for approximately 55% of the studies related to stem cells associated with Chagas disease. Most of the studies focus on developing new strategies for treating Chagas disease using stem cells. This suggests that the research agenda in this area is still under development, highlighting the importance of continuing to pursue existing research avenues and expanding the range of strategies for the treatment of the disease.","PeriodicalId":10501,"journal":{"name":"COLLNET Journal of Scientometrics and Information Management","volume":"15 1","pages":"429 - 443"},"PeriodicalIF":1.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"59521748","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 : 2021-07-03DOI: 10.1080/09737766.2021.1981172
Jânio Rodrigo de Jesus Santos, Cláudio Damasceno Pinto, Angela Machado Rocha
Nanobiotechnology is a promising area of research that has been used to develop technologies to combat Zika virus (ZIKV). This study aims to analyze the patent scenario related to the use of nanobiotechnology in strategies against the ZIKV, using the Orbit Intelligence software. The results point to growth in the number of patent deposits between the years 2015 and 2019. Modernatx, MIT, and Harvard University own 38% of the technologies developed against the ZIKV. The EPO, WIPO, and the United States received 47% of patent protection applications developed by companies with support from techniques in the fields of pharmacology and biotechnology. About 42% of patents found belong to the areas of diagnosis and prevention, designed with the aid of nanoparticles used as delivery systems in vaccines and rapid tests. The results showed that nanobiotechnology is an emerging technology and has been widely used in strategies to stop the ZIKV advance.
{"title":"Technological scenarios of the use of nanobiotechnology in strategies against Zika virus","authors":"Jânio Rodrigo de Jesus Santos, Cláudio Damasceno Pinto, Angela Machado Rocha","doi":"10.1080/09737766.2021.1981172","DOIUrl":"https://doi.org/10.1080/09737766.2021.1981172","url":null,"abstract":"Nanobiotechnology is a promising area of research that has been used to develop technologies to combat Zika virus (ZIKV). This study aims to analyze the patent scenario related to the use of nanobiotechnology in strategies against the ZIKV, using the Orbit Intelligence software. The results point to growth in the number of patent deposits between the years 2015 and 2019. Modernatx, MIT, and Harvard University own 38% of the technologies developed against the ZIKV. The EPO, WIPO, and the United States received 47% of patent protection applications developed by companies with support from techniques in the fields of pharmacology and biotechnology. About 42% of patents found belong to the areas of diagnosis and prevention, designed with the aid of nanoparticles used as delivery systems in vaccines and rapid tests. The results showed that nanobiotechnology is an emerging technology and has been widely used in strategies to stop the ZIKV advance.","PeriodicalId":10501,"journal":{"name":"COLLNET Journal of Scientometrics and Information Management","volume":"15 1","pages":"413 - 428"},"PeriodicalIF":1.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49002670","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 : 2021-07-03DOI: 10.1080/09737766.2021.2007038
Ahmet Ayaz, K. Çelik, Ozcan Ozyurt
The use of cloud computing has become widespread with the rapid development of technology. In this context, it is important to make a bibliometric analysis to identify developments in cloud computing research and to guide future research. For bibliometric analysis of cloud computing research, this study examines 48692 studies scanned in the Web of Science database as of July 2021, without year and index limits. VOSviewer software was used for bibliometric analysis. Bibliometric analysis showed that the research in the field of cloud computing increased exponentially until 2016, but after 2016, the research decreased and turned to more specific areas. China, USA, and India, respectively, are the countries that contributed the most to the cloud computing literature. According to the keyword co-occurrence analysis, the prominent keywords are fog computing, mobile cloud computing, data security, and trust. In addition, edge computing and blockchain stand out as trending topics in recent years. Future Generation Computer Systems and IEEE Access are the journals that contribute the most to the field. Taken as a whole, the findings of the study describe the field in general and provide important, enlightening, and stimulating information for researchers who are or will be interested in cloud computing.
随着技术的快速发展，云计算的使用已经变得广泛。在这种情况下，重要的是要进行文献计量分析，以确定云计算研究的发展，并指导未来的研究。对于云计算研究的文献计量分析，本研究检查了截至2021年7月在Web of Science数据库中扫描的48692篇研究，没有年份和索引限制。使用VOSviewer软件进行文献计量学分析。文献计量分析表明，2016年之前，云计算领域的研究呈指数级增长，但2016年之后，研究减少，转向更具体的领域。中国、美国和印度分别是对云计算文献贡献最大的国家。根据关键词共现分析，突出的关键词是雾计算、移动云计算、数据安全、信任。此外，边缘计算和区块链是近年来的热门话题。《未来一代计算机系统》和《IEEE Access》是对该领域贡献最大的期刊。作为一个整体，该研究的发现概括地描述了该领域，并为正在或将要对云计算感兴趣的研究人员提供了重要的、启发性的和令人兴奋的信息。
{"title":"Pattern detection in cloud computing: Bibliometric mapping of publications in the field from past to present","authors":"Ahmet Ayaz, K. Çelik, Ozcan Ozyurt","doi":"10.1080/09737766.2021.2007038","DOIUrl":"https://doi.org/10.1080/09737766.2021.2007038","url":null,"abstract":"The use of cloud computing has become widespread with the rapid development of technology. In this context, it is important to make a bibliometric analysis to identify developments in cloud computing research and to guide future research. For bibliometric analysis of cloud computing research, this study examines 48692 studies scanned in the Web of Science database as of July 2021, without year and index limits. VOSviewer software was used for bibliometric analysis. Bibliometric analysis showed that the research in the field of cloud computing increased exponentially until 2016, but after 2016, the research decreased and turned to more specific areas. China, USA, and India, respectively, are the countries that contributed the most to the cloud computing literature. According to the keyword co-occurrence analysis, the prominent keywords are fog computing, mobile cloud computing, data security, and trust. In addition, edge computing and blockchain stand out as trending topics in recent years. Future Generation Computer Systems and IEEE Access are the journals that contribute the most to the field. Taken as a whole, the findings of the study describe the field in general and provide important, enlightening, and stimulating information for researchers who are or will be interested in cloud computing.","PeriodicalId":10501,"journal":{"name":"COLLNET Journal of Scientometrics and Information Management","volume":"15 1","pages":"469 - 494"},"PeriodicalIF":1.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43784163","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 : 2021-07-03DOI: 10.1080/09737766.2021.1955419
Georgios Stoupas, Antonis Sidiropoulos, Dimitrios Katsaros, Y. Manolopoulos
The quality of the education provided and the research impact produced by universities is continuously evaluated at national and international level. This phenomenon is not new. However, nowadays education is not only considered as a social value and right/privilege, but also as a big economic sector, which addresses to large portions of population worldwide. In this ecosystem, university rankings play a crucial role since they provide filtered information which is reproduced in surveys, newspapers, social media etc. All university rankings are based on a set of ad hoc evaluation criteria. Moreover, the final score is based on a set of arbitrary weights summing up to 1. Thus, at the end, these university rankings differ significantly producing ambiguities and doubts. In this paper, we propose a novel university ranking method based on the Skyline operator, which is used on multi-dimensional objects to extract the non-dominated (i.e., “prevailing”) ones. Our method is characterized by several advantages, such as: it is transparent, reproducible, without any arbitrarily selected parameters, based on the research output of universities only and not on publicly not traceable or questionnaires. Our method does not provide absolute rankings, but rather it ranks universities categorized in equivalence classes. Thus, we develop a generic framework which can be used for ranking universities and departments, and even individual persons. For the proof of concept we apply the framework in our Greek academic space, providing a case study on ranking persons and departments on computer science and engineering using data extracted from Microsoft Academic.
{"title":"When universities rise (Rank) high into the skyline","authors":"Georgios Stoupas, Antonis Sidiropoulos, Dimitrios Katsaros, Y. Manolopoulos","doi":"10.1080/09737766.2021.1955419","DOIUrl":"https://doi.org/10.1080/09737766.2021.1955419","url":null,"abstract":"The quality of the education provided and the research impact produced by universities is continuously evaluated at national and international level. This phenomenon is not new. However, nowadays education is not only considered as a social value and right/privilege, but also as a big economic sector, which addresses to large portions of population worldwide. In this ecosystem, university rankings play a crucial role since they provide filtered information which is reproduced in surveys, newspapers, social media etc. All university rankings are based on a set of ad hoc evaluation criteria. Moreover, the final score is based on a set of arbitrary weights summing up to 1. Thus, at the end, these university rankings differ significantly producing ambiguities and doubts. In this paper, we propose a novel university ranking method based on the Skyline operator, which is used on multi-dimensional objects to extract the non-dominated (i.e., “prevailing”) ones. Our method is characterized by several advantages, such as: it is transparent, reproducible, without any arbitrarily selected parameters, based on the research output of universities only and not on publicly not traceable or questionnaires. Our method does not provide absolute rankings, but rather it ranks universities categorized in equivalence classes. Thus, we develop a generic framework which can be used for ranking universities and departments, and even individual persons. For the proof of concept we apply the framework in our Greek academic space, providing a case study on ranking persons and departments on computer science and engineering using data extracted from Microsoft Academic.","PeriodicalId":10501,"journal":{"name":"COLLNET Journal of Scientometrics and Information Management","volume":"15 1","pages":"241 - 258"},"PeriodicalIF":1.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43304429","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 : 2021-07-03DOI: 10.1080/09737766.2021.1960219
Nazia Wahid, N. Warraich, Muzammil Tahira
The study aims to analyze the most productive Pakistani authors by using scientometric approach based on the Web of Science (WoS) data to perform group level comparative analysis. One hundred most productive authors have been recognized from ten years data of top ten universities ranked in WoS. Their publication data has been extracted for further analysis. We applied traditional metrics, h-index, h-type and composite indices. The authors have been divided into four groups, named Top Authors (N=31), Big Producers (N=18), Selective Authors (N=19) and Low Productive Authors (N=32). Descriptive and inferential statistics were performed. Findings revealed that h-index, h-type and composite indices clearly differentiate upper and lower groups. However, the discrimination between middle groups is indistinct. The functional relationship of total citations of all groups with the h-type and composite indices is found better as compared to the other traditional metrics. Total citations of top authors, selective authors and low productive authors has strong relationship with g-index and p-index except big producers. Moreover, total citations has strong relationship with h-index at top author level, moderate relation with big producers and low productive authors and poor at selective author level. The relationship of citations per publications of all groups with the h-type and composite indices was found moderate or poor except p-index. It was observed that publications counts of all groups has weak relationship with all indices. The study adds insight into the discrimination of groups of Pakistani authors using different scientometric indices. It may be of interest to those concerned in research performance evaluation metrics.
该研究旨在利用基于科学网络(Web of Science, WoS)数据的科学计量学方法进行群体水平的比较分析，分析最高产的巴基斯坦作者。根据WoS排名前十的大学的十年数据，评选出100位最具生产力的作者。他们发表的数据已被提取出来作进一步分析。我们采用了传统指标、h指数、h型指数和复合指数。这些作者被分为“顶级作者”(31名)、“大作者”(18名)、“选择性作者”(19名)、“低作者”(32名)等4组。进行描述性和推断性统计。结果表明，h指数、h型和综合指数明显区分上下级。然而，中间群体之间的歧视并不明显。与其他传统指标相比，各类群总被引量与h型指标和复合指标之间的函数关系更好。除大型作者外，顶级作者、选择性作者和低产出作者的总被引量与g指数和p指数之间存在较强的关系。总被引量在顶级作者水平与h指数有较强的关系，与高产作者和高产作者的关系中等，与选择性作者水平的关系较差。除p指数外，各类群的出版物被引量与h型指数和综合指数的关系均为中等或较差。结果表明，各类群的出版物数量与各指标的相关性较弱。这项研究增加了对使用不同科学计量指数的巴基斯坦作者群体的歧视的洞察。它可能对那些关心研究绩效评估指标的人感兴趣。
{"title":"Group level scientometric analysis of Pakistani authors","authors":"Nazia Wahid, N. Warraich, Muzammil Tahira","doi":"10.1080/09737766.2021.1960219","DOIUrl":"https://doi.org/10.1080/09737766.2021.1960219","url":null,"abstract":"The study aims to analyze the most productive Pakistani authors by using scientometric approach based on the Web of Science (WoS) data to perform group level comparative analysis. One hundred most productive authors have been recognized from ten years data of top ten universities ranked in WoS. Their publication data has been extracted for further analysis. We applied traditional metrics, h-index, h-type and composite indices. The authors have been divided into four groups, named Top Authors (N=31), Big Producers (N=18), Selective Authors (N=19) and Low Productive Authors (N=32). Descriptive and inferential statistics were performed. Findings revealed that h-index, h-type and composite indices clearly differentiate upper and lower groups. However, the discrimination between middle groups is indistinct. The functional relationship of total citations of all groups with the h-type and composite indices is found better as compared to the other traditional metrics. Total citations of top authors, selective authors and low productive authors has strong relationship with g-index and p-index except big producers. Moreover, total citations has strong relationship with h-index at top author level, moderate relation with big producers and low productive authors and poor at selective author level. The relationship of citations per publications of all groups with the h-type and composite indices was found moderate or poor except p-index. It was observed that publications counts of all groups has weak relationship with all indices. The study adds insight into the discrimination of groups of Pakistani authors using different scientometric indices. It may be of interest to those concerned in research performance evaluation metrics.","PeriodicalId":10501,"journal":{"name":"COLLNET Journal of Scientometrics and Information Management","volume":"15 1","pages":"287 - 304"},"PeriodicalIF":1.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48678288","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 : 2021-07-03DOI: 10.1080/09737766.2021.2005455
Saddam Hossain, M. Sadik Batcha
This study aims to investigate the publication rate of Indian dialysis research and analyze the distribution of research areas. This research was a scientometric study that applied quantitative and qualitative bibliographies of Web of Science (WoS). The data were extracted from the Web of Science database between 2001 to 2020 of Indian dialysis research. We used bibliographic analyses using VOSviewer software for network analysis between 2001 to 2020. We performed analyses of journals, authors, publication years, organizations, and countries. We accessed 1503 documents published during the period, the majority of published in 2020 with 151 documents. The study revealed that Jha V is the most prolific author in this field with 100 papers and the highest h-index (25). Results showed that the most document types are journal Articles (1135) of a total number of publications. We observed from the journals, the most preferred choice of the authors to publish their research on Peritoneal Dialysis International (n = 77), whereas Indian Pediatrics (India) had the lowest articles (n = 14). The study also revealed that documents published a number of countries with limited relationship within the network, suggesting opportunities to build their research collaboration with leaders of significant networks or with other countries.
本研究旨在调查印度透析研究的发表率，并分析研究领域的分布。本研究是应用Web of Science (WoS)的定量和定性书目进行科学计量学研究。这些数据是从2001年至2020年印度透析研究的Web of Science数据库中提取的。采用文献分析方法，利用VOSviewer软件进行2001 - 2020年的网络分析。我们对期刊、作者、出版年份、组织和国家进行了分析。我们查阅了这一时期发表的1503份文件，其中大部分是在2020年发表的151份文件。研究显示，Jha V是该领域最多产的作者，发表了100篇论文，h指数最高(25)。结果表明，论文类型最多的是期刊文章(1135篇)。我们从期刊中观察到，作者最喜欢在腹膜透析国际(n = 77)上发表他们的研究，而印度儿科(印度)的文章最少(n = 14)。该研究还揭示了一些在网络内关系有限的国家发表的文件，这表明它们有机会与重要网络的领导人或与其他国家建立研究合作。
{"title":"Scientometric analysis of research productivity from Indian dialysis over the last twenty years in Web of Science","authors":"Saddam Hossain, M. Sadik Batcha","doi":"10.1080/09737766.2021.2005455","DOIUrl":"https://doi.org/10.1080/09737766.2021.2005455","url":null,"abstract":"This study aims to investigate the publication rate of Indian dialysis research and analyze the distribution of research areas. This research was a scientometric study that applied quantitative and qualitative bibliographies of Web of Science (WoS). The data were extracted from the Web of Science database between 2001 to 2020 of Indian dialysis research. We used bibliographic analyses using VOSviewer software for network analysis between 2001 to 2020. We performed analyses of journals, authors, publication years, organizations, and countries. We accessed 1503 documents published during the period, the majority of published in 2020 with 151 documents. The study revealed that Jha V is the most prolific author in this field with 100 papers and the highest h-index (25). Results showed that the most document types are journal Articles (1135) of a total number of publications. We observed from the journals, the most preferred choice of the authors to publish their research on Peritoneal Dialysis International (n = 77), whereas Indian Pediatrics (India) had the lowest articles (n = 14). The study also revealed that documents published a number of countries with limited relationship within the network, suggesting opportunities to build their research collaboration with leaders of significant networks or with other countries.","PeriodicalId":10501,"journal":{"name":"COLLNET Journal of Scientometrics and Information Management","volume":"15 1","pages":"323 - 339"},"PeriodicalIF":1.0,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48834241","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 : 2021-01-02DOI: 10.1080/09737766.2021.1934181
Waleed Ali, A. Elbadawy
Purpose – This paper focused on African research output and aimed to measure and compare the continent’s leading countries in terms of the most indexed publications in the Web of Science. It also aimed to discover where the position of Egypt is on the African world map of research and estimate the rising percentage of African research output. Design/methodology/approach – The paper focused on African research output from 2015 to 2019. Data were extracted from the InCites research analytical tool from the Web of Science Group, collected from 2015 to 2019, and used to examine the growth of research output. Findings – The paper proved that the top 10 African countries in publishing scientific research are (South Africa, Egypt, Tunisia, Nigeria, Algeria, Kenya, Morocco, Ethiopia, Ghana, Uganda), and the top 10 countries contribute with 92.2% of total publications in Africa in the last 5 years, which means the rest African countries contribute only with 7.8 % of total publications. Found that Egypt has the most cited documents with 67% of the total publications which reflect the quality of Egyptian scientific research. Originality/Value – This study provides statistics on African research outputs and concentrating on the top 10 countries that have the most publications from 2015-2019, and this is the first paper discussing these countries in this period.
{"title":"Research output of the top 10 African countries : An analytical study","authors":"Waleed Ali, A. Elbadawy","doi":"10.1080/09737766.2021.1934181","DOIUrl":"https://doi.org/10.1080/09737766.2021.1934181","url":null,"abstract":"Purpose – This paper focused on African research output and aimed to measure and compare the continent’s leading countries in terms of the most indexed publications in the Web of Science. It also aimed to discover where the position of Egypt is on the African world map of research and estimate the rising percentage of African research output. Design/methodology/approach – The paper focused on African research output from 2015 to 2019. Data were extracted from the InCites research analytical tool from the Web of Science Group, collected from 2015 to 2019, and used to examine the growth of research output. Findings – The paper proved that the top 10 African countries in publishing scientific research are (South Africa, Egypt, Tunisia, Nigeria, Algeria, Kenya, Morocco, Ethiopia, Ghana, Uganda), and the top 10 countries contribute with 92.2% of total publications in Africa in the last 5 years, which means the rest African countries contribute only with 7.8 % of total publications. Found that Egypt has the most cited documents with 67% of the total publications which reflect the quality of Egyptian scientific research. Originality/Value – This study provides statistics on African research outputs and concentrating on the top 10 countries that have the most publications from 2015-2019, and this is the first paper discussing these countries in this period.","PeriodicalId":10501,"journal":{"name":"COLLNET Journal of Scientometrics and Information Management","volume":"15 1","pages":"9 - 25"},"PeriodicalIF":1.0,"publicationDate":"2021-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/09737766.2021.1934181","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44403592","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 : 2021-01-02DOI: 10.1080/09737766.2021.1934604
H. Okagbue, E. Akhmetshin, J. A. Teixeira da Silva
CiteScore, Scopus/Elsevier’s open journal metric, is an attractive alternativeto Clarivate Analytics’ impactfactor. Inmid-2020, theequation used to calculate the CiteScore changed, reflecting a four-year window of data versus a previous three-year data set. Extrapolating CiteScore data from Scopus for the top 1000 ranked journals, we wanted to appreciate how CiteScore trended over time. We found that, on average, CiteScore increased consistently each year between 2015 and 2019, from 13.877 to 16.536. Broadly, this reflects a greater number of citations per publication over time, so a constant rise in citation rate. Academics should not erroneously mistake this rise as a higher level of quality. In addition, k-mean clustering of the percentile and CiteScore showed the existence of three distinct clusters for the top 1000 ranked journals, which aggregated together due to their distinct similarities (similar mean). This pattern may assist researchers to study how the pattern of the distribution of CiteScore and percentile changes over time, and monitor how the CiteScore methodology has evolved over the years.
{"title":"Distinct clusters of CiteScore and percentiles in top 1000 journals in Scopus","authors":"H. Okagbue, E. Akhmetshin, J. A. Teixeira da Silva","doi":"10.1080/09737766.2021.1934604","DOIUrl":"https://doi.org/10.1080/09737766.2021.1934604","url":null,"abstract":"CiteScore, Scopus/Elsevier’s open journal metric, is an attractive alternativeto Clarivate Analytics’ impactfactor. Inmid-2020, theequation used to calculate the CiteScore changed, reflecting a four-year window of data versus a previous three-year data set. Extrapolating CiteScore data from Scopus for the top 1000 ranked journals, we wanted to appreciate how CiteScore trended over time. We found that, on average, CiteScore increased consistently each year between 2015 and 2019, from 13.877 to 16.536. Broadly, this reflects a greater number of citations per publication over time, so a constant rise in citation rate. Academics should not erroneously mistake this rise as a higher level of quality. In addition, k-mean clustering of the percentile and CiteScore showed the existence of three distinct clusters for the top 1000 ranked journals, which aggregated together due to their distinct similarities (similar mean). This pattern may assist researchers to study how the pattern of the distribution of CiteScore and percentile changes over time, and monitor how the CiteScore methodology has evolved over the years.","PeriodicalId":10501,"journal":{"name":"COLLNET Journal of Scientometrics and Information Management","volume":"15 1","pages":"133 - 143"},"PeriodicalIF":1.0,"publicationDate":"2021-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/09737766.2021.1934604","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43527500","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 : 2021-01-02DOI: 10.1080/09737766.2021.1936272
B. Lund, S. Maurya
The present study compared research productivity of Library and Information Science (LIS) faculties working in 61 government universities of India and 55 American Library Association-accredited LIS programs in the United States. A regression model is used to determine the effect of independent variables i.e. number of publications, number of citations per publication, and total number of citations for top-cited publication on h-index value of faculties. Further, k-means cluster analysis (three tier) is performed for each rank of faculties (full, associate & assistant professor) based on their publication and citation. The findings of this study indicate that for both countries h-index value of LIS faculties is related to number of publications and citations per publication, while mitigating the impact of a highly-cited publication. The top tier of Indian LIS faculties by publications, have more publications, citations for most-cited publication, and larger h-index than the lowest tier in the U.S. (though these researchers do have a higher number of citations per publication). The most productive LIS Faculties in the U.S. have about 3.5 times more publications, citations, and h-index than Indian LIS faculties. Finally, for the evaluation of LIS researchers for tenure and promotion decisions in regard to h-index, the study suggests that it may provide more equitable valuation of research productivity than looking at raw number of citation counts, while providing more information about quality of publications than just the raw number of publications alone.
{"title":"Research productivity of library and information science faculty in India and the United States : A comparison based on publications, citations and h-index","authors":"B. Lund, S. Maurya","doi":"10.1080/09737766.2021.1936272","DOIUrl":"https://doi.org/10.1080/09737766.2021.1936272","url":null,"abstract":"The present study compared research productivity of Library and Information Science (LIS) faculties working in 61 government universities of India and 55 American Library Association-accredited LIS programs in the United States. A regression model is used to determine the effect of independent variables i.e. number of publications, number of citations per publication, and total number of citations for top-cited publication on h-index value of faculties. Further, k-means cluster analysis (three tier) is performed for each rank of faculties (full, associate & assistant professor) based on their publication and citation. The findings of this study indicate that for both countries h-index value of LIS faculties is related to number of publications and citations per publication, while mitigating the impact of a highly-cited publication. The top tier of Indian LIS faculties by publications, have more publications, citations for most-cited publication, and larger h-index than the lowest tier in the U.S. (though these researchers do have a higher number of citations per publication). The most productive LIS Faculties in the U.S. have about 3.5 times more publications, citations, and h-index than Indian LIS faculties. Finally, for the evaluation of LIS researchers for tenure and promotion decisions in regard to h-index, the study suggests that it may provide more equitable valuation of research productivity than looking at raw number of citation counts, while providing more information about quality of publications than just the raw number of publications alone.","PeriodicalId":10501,"journal":{"name":"COLLNET Journal of Scientometrics and Information Management","volume":"15 1","pages":"89 - 105"},"PeriodicalIF":1.0,"publicationDate":"2021-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/09737766.2021.1936272","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45056401","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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