COLLNET Journal of Scientometrics and Information Management最新文献_第5页

Discovering the evolution of artificial intelligence in cancer research using dynamic topic modeling 利用动态主题建模发现癌症研究中人工智能的演变

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COLLNET Journal of Scientometrics and Information Management Pub Date : 2021-07-03 DOI: 10.1080/09737766.2021.1958659

Shahab Mosallaie, M. Rad, Andrea Schiffauerova, Ashkan Ebadi

{"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}

引用次数: 5

Scientific mapping of stem cells associated with Chagas disease : A bibliometric analysis 与恰加斯病相关的干细胞科学制图:文献计量学分析

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COLLNET Journal of Scientometrics and Information Management Pub Date : 2021-07-03 DOI: 10.1080/09737766.2021.1977094

Jânio Rodrigo de Jesus Santos, Carlos Augusto Francisco de Jesus, Cláudio Damasceno Pinto

引用次数: 0

Technological scenarios of the use of nanobiotechnology in strategies against Zika virus 在寨卡病毒战略中使用纳米生物技术的技术情景

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COLLNET Journal of Scientometrics and Information Management Pub Date : 2021-07-03 DOI: 10.1080/09737766.2021.1981172

Jânio Rodrigo de Jesus Santos, Cláudio Damasceno Pinto, Angela Machado Rocha

引用次数: 0

Pattern detection in cloud computing: Bibliometric mapping of publications in the field from past to present 云计算中的模式检测:从过去到现在该领域出版物的文献计量映射

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COLLNET Journal of Scientometrics and Information Management Pub Date : 2021-07-03 DOI: 10.1080/09737766.2021.2007038

Ahmet Ayaz, K. Çelik, Ozcan Ozyurt

{"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}

引用次数: 0

When universities rise (Rank) high into the skyline 当大学拔地而起

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COLLNET Journal of Scientometrics and Information Management Pub Date : 2021-07-03 DOI: 10.1080/09737766.2021.1955419

Georgios Stoupas, Antonis Sidiropoulos, Dimitrios Katsaros, Y. Manolopoulos

{"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}

引用次数: 1

Group level scientometric analysis of Pakistani authors 巴基斯坦作者群体水平的科学计量学分析

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COLLNET Journal of Scientometrics and Information Management Pub Date : 2021-07-03 DOI: 10.1080/09737766.2021.1960219

Nazia Wahid, N. Warraich, Muzammil Tahira

{"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}

引用次数: 1

Scientometric analysis of research productivity from Indian dialysis over the last twenty years in Web of Science 科学之网对过去二十年印度透析研究生产力的科学计量分析

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COLLNET Journal of Scientometrics and Information Management Pub Date : 2021-07-03 DOI: 10.1080/09737766.2021.2005455

Saddam Hossain, M. Sadik Batcha

{"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}

引用次数: 2

Research output of the top 10 African countries : An analytical study 十大非洲国家的研究成果：一项分析研究

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COLLNET Journal of Scientometrics and Information Management Pub Date : 2021-01-02 DOI: 10.1080/09737766.2021.1934181

Waleed Ali, A. Elbadawy

{"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}

引用次数: 8

Distinct clusters of CiteScore and percentiles in top 1000 journals in Scopus Scopus排名前1000的期刊中不同的CiteScore集群和百分位数

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COLLNET Journal of Scientometrics and Information Management Pub Date : 2021-01-02 DOI: 10.1080/09737766.2021.1934604

H. Okagbue, E. Akhmetshin, J. A. Teixeira da Silva

{"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}

引用次数: 1

Research productivity of library and information science faculty in India and the United States : A comparison based on publications, citations and h-index 印度和美国图书馆情报学教师的研究效率:基于出版物、引文和h指数的比较

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COLLNET Journal of Scientometrics and Information Management Pub Date : 2021-01-02 DOI: 10.1080/09737766.2021.1936272

B. Lund, S. Maurya

{"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}

引用次数: 2