Purpose:We analyzed the structure of a community of authors working in the field of social network analysis(SNA)based on citation indicators:direct citation and bibliographic coupling metrics.We observed patterns at t...Purpose:We analyzed the structure of a community of authors working in the field of social network analysis(SNA)based on citation indicators:direct citation and bibliographic coupling metrics.We observed patterns at the micro,meso,and macro levels of analysis.Design/methodology/approach:We used bibliometric network analysis,including the“temporal quantities”approach proposed to study temporal networks.Using a two-mode network linking publications with authors and a one-mode network of citations between the works,we constructed and analyzed the networks of citation and bibliographic coupling among authors.We used an iterated saturation data collection approach.Findings:At the macro-level,we observed the global structural features of citations between authors,showing that 80%of authors have not more than 15 citations from other works.At the meso-level,we extracted the groups of authors citing each other and similar to each other according to their citation patterns.We have seen a division of authors in SNA into groups of social scientists and physicists,as well as into other groups of authors from different disciplines.We found some examples of brokerage between different groups that maintained the common identity of the field.At the micro-level,we extracted authors with extremely high values of received citations,who can be considered as the most prominent authors in the field.We examined the temporal properties of the most popular authors.Research limitations:The main challenge in this approach is the resolution of the author’s name(synonyms and homonyms).We faced the author disambiguation,or“multiple personalities”(Harzing,2015)problem.To remain consistent and comparable with our previously published articles,we used the same SNA data collected up to 2018.The analysis and conclusions on the activity,productivity,and visibility of the authors are relative only to the field of SNA.Practical implications:The proposed approach can be utilized for similar objectives and identifying key structures and characteristics in other disciplines.This may potentially inspire the application of network approaches in other research areas,creating more authors collaborating in the field of SNA.Originality/value:We identified and applied an innovative approach and methods to study the structure of scientific communities,which allowed us to get the findings going beyond those obtained with other methods.We used a new approach to temporal network analysis,which is an important addition to the analysis as it provides detailed information on different measures for the authors and pairs of authors over time.展开更多
Purpose:Research dynamics have long been a research interest.It is a macro perspective tool for discovering temporal research trends of a certain discipline or subject.A micro perspective of research dynamics,however,...Purpose:Research dynamics have long been a research interest.It is a macro perspective tool for discovering temporal research trends of a certain discipline or subject.A micro perspective of research dynamics,however,concerning a single researcher or a highly cited paper in terms of their citations and“citations of citations”(forward chaining)remains unexplored.Design/methodology/approach:In this paper,we use a cross-collection topic model to reveal the research dynamics of topic disappearance topic inheritance,and topic innovation in each generation of forward chaining.Findings:For highly cited work,scientific influence exists in indirect citations.Topic modeling can reveal how long this influence exists in forward chaining,as well as its influence.Research limitations:This paper measures scientific influence and indirect scientific influence only if the relevant words or phrases are borrowed or used in direct or indirect citations.Paraphrasing or semantically similar concept may be neglected in this research.Practical implications:This paper demonstrates that a scientific influence exists in indirect citations through its analysis of forward chaining.This can serve as an inspiration on how to adequately evaluate research influence.Originality:The main contributions of this paper are the following three aspects.First,besides research dynamics of topic inheritance and topic innovation,we model topic disappearance by using a cross-collection topic model.Second,we explore the length and character of the research impact through“citations of citations”content analysis.Finally,we analyze the research dynamics of artificial intelligence researcher Geoffrey Hinton’s publications and the topic dynamics of forward chaining.展开更多
Purpose:Nearly 122 scientific journals are currently being published in Armenia-of which only six are indexed by WoS and/or Scopus databases.The majority of the national journals are published in the Armenian language...Purpose:Nearly 122 scientific journals are currently being published in Armenia-of which only six are indexed by WoS and/or Scopus databases.The majority of the national journals are published in the Armenian language,solely possessing abstracts written in English,although there are also English-language and multi-language journals with articles not only in Armenian but also in other foreign languages.The aim of this article is to study the visibility of the(non-indexed)national Armenian journals in the WoS database through citation analysis.In consideration of the existence of a relevant Armenian“diaspora”in the world,this article also attempts to estimate its impact in terms of citation statistics.Design/methodology/approach:For this end,we have identified citations to the national/domestic Armenian journals in the WoS database in comparison with the share of citations received from“diaspora”researchers(researchers of Armenian origin born in foreign countries and those originally from Armenia who have emigrated to foreign countries).Findings:Among the 116 Armenian domestic journals analyzed(not indexed by WoS),only 47 were found to be cited in WoS.Of these journals,almost 12%are citations by“diaspora”researchers,most of which concern Social Science and Humanities journals.Research limitations:Although the surnames of Armenians end with-i(y)an,sometimes,the Diaspora Armenians,surnames are changed or modified or they are not ending with-i(y)an,in this case we may fail to identify them.Practical implications:This study can help to build new,more deep and comprehensive relations with scientific diasporas.Originality/value:This study offers a new understanding of multifaced research collaboration with scientific diasporas and their role in internationalization of domestic journals.展开更多
The process of ranking scientific publications in dynamic citation networks plays a crucial rule in a variety of applications. Despite the availability of a number of ranking algorithms, most of them use common popula...The process of ranking scientific publications in dynamic citation networks plays a crucial rule in a variety of applications. Despite the availability of a number of ranking algorithms, most of them use common popularity metrics such as the citation count, h-index, and Impact Factor (IF). These adopted metrics cause a problem of bias in favor of older publications that took enough time to collect as many citations as possible. This paper focuses on solving the problem of bias by proposing a new ranking algorithm based on the PageRank (PR) algorithm;it is one of the main page ranking algorithms being widely used. The developed algorithm considers a newly suggested metric called the Citation Average rate of Change (CAC). Time information such as publication date and the citation occurrence’s time are used along with citation data to calculate the new metric. The proposed ranking algorithm was tested on a dataset of scientific papers in the field of medical physics published in the Dimensions database from years 2005 to 2017. The experimental results have shown that the proposed ranking algorithm outperforms the PageRank algorithm in ranking scientific publications where 26 papers instead of only 14 were ranked among the top 100 papers of this dataset. In addition, there were no radical changes or unreasonable jump in the ranking process, i.e., the correlation rate between the results of the proposed ranking method and the original PageRank algorithm was 92% based on the Spearman correlation coefficient.展开更多
Purpose:Using the metaphor of"unicorn,"we identify the scientific papers and technical patents characterized by the informetric feature of very high citations in the first ten years after publishing,which ma...Purpose:Using the metaphor of"unicorn,"we identify the scientific papers and technical patents characterized by the informetric feature of very high citations in the first ten years after publishing,which may provide a new pattern to understand very high impact works in science and technology.Design/methodology/approach:When we set CT as the total citations of papers or patents in the first ten years after publication,with CT≥5,000 for scientific"unicorn"and CT≥500 for technical"unicorn,"we have an absolute standard for identifying scientific and technical"unicorn"publications.Findings:We identify 165 scientific"unicorns"in 14,301,875 WoS papers and 224 technical"unicorns"in 13,728,950 DII patents during 2001–2012.About 50%of"unicorns"belong to biomedicine,in which selected cases are individually discussed.The rare"unicorns"increase following linear model,the fitting data show 95%confidence with the RMSE of scientific"unicorn"is 0.2127 while the RMSE of technical"unicorn"is 0.0923.Research limitations:A"unicorn"is a pure quantitative consideration without concerning its quality,and"potential unicorns"as CT≤5,000 for papers and CT≤500 for patents are left in future studies.Practical implications:Scientific and technical"unicorns"provide a new pattern to understand high-impact works in science and technology.The"unicorn"pattern supplies a concise approach to identify very high-impact scientific papers and technical patents.Originality/value:The"unicorn"pattern supplies a concise approach to identify very high impact scientific papers and technical patents.展开更多
文章以Web of Science中收录的文献数据为分析对象,以计算机科学领域为例,验证国际合作是否能提高科学研究的影响力。为了检验国家数量与被引频次之间的相关性,开展了相关性分析和比较分析,并且分析了合作网络以了解各个国家所发挥的不...文章以Web of Science中收录的文献数据为分析对象,以计算机科学领域为例,验证国际合作是否能提高科学研究的影响力。为了检验国家数量与被引频次之间的相关性,开展了相关性分析和比较分析,并且分析了合作网络以了解各个国家所发挥的不同作用和影响。结果表明,国际合作论文的被引频次总体上高于国内作者的论文,但国家数量与被引频次之间仅存在弱相关关系。我国在2007—2009年期间共与65个国家开展了合作研究,其中19个国家在提高平均被引频次方面发挥了重要作用。展开更多
医学信息学具有显著的学科交叉特性,大量学者采用定性或定量方法对医学信息学的学科内涵、领域特点、发展路径、研究前沿和发展趋势、现存问题等进行了深入的研究,但对该学科的跨学科特性进行系统研究相对较少。基于Web of science文献...医学信息学具有显著的学科交叉特性,大量学者采用定性或定量方法对医学信息学的学科内涵、领域特点、发展路径、研究前沿和发展趋势、现存问题等进行了深入的研究,但对该学科的跨学科特性进行系统研究相对较少。基于Web of science文献及学科类别数据,运用文献计量和知识图谱可视化技术,从多维角度较深入地揭示了医学信息学的学科交叉发展态势,旨在为促进医学信息学学科研究的发展提供参考。展开更多
基金supported in part by the Slovenian Research Agency(VB,research program P1-0294)(VB,research project J5-2557)+2 种基金(VB,research project J5-4596)COST EU(VB,COST action CA21163(HiTEc)is prepared within the framework of the HSE University Basic Research Program.
文摘Purpose:We analyzed the structure of a community of authors working in the field of social network analysis(SNA)based on citation indicators:direct citation and bibliographic coupling metrics.We observed patterns at the micro,meso,and macro levels of analysis.Design/methodology/approach:We used bibliometric network analysis,including the“temporal quantities”approach proposed to study temporal networks.Using a two-mode network linking publications with authors and a one-mode network of citations between the works,we constructed and analyzed the networks of citation and bibliographic coupling among authors.We used an iterated saturation data collection approach.Findings:At the macro-level,we observed the global structural features of citations between authors,showing that 80%of authors have not more than 15 citations from other works.At the meso-level,we extracted the groups of authors citing each other and similar to each other according to their citation patterns.We have seen a division of authors in SNA into groups of social scientists and physicists,as well as into other groups of authors from different disciplines.We found some examples of brokerage between different groups that maintained the common identity of the field.At the micro-level,we extracted authors with extremely high values of received citations,who can be considered as the most prominent authors in the field.We examined the temporal properties of the most popular authors.Research limitations:The main challenge in this approach is the resolution of the author’s name(synonyms and homonyms).We faced the author disambiguation,or“multiple personalities”(Harzing,2015)problem.To remain consistent and comparable with our previously published articles,we used the same SNA data collected up to 2018.The analysis and conclusions on the activity,productivity,and visibility of the authors are relative only to the field of SNA.Practical implications:The proposed approach can be utilized for similar objectives and identifying key structures and characteristics in other disciplines.This may potentially inspire the application of network approaches in other research areas,creating more authors collaborating in the field of SNA.Originality/value:We identified and applied an innovative approach and methods to study the structure of scientific communities,which allowed us to get the findings going beyond those obtained with other methods.We used a new approach to temporal network analysis,which is an important addition to the analysis as it provides detailed information on different measures for the authors and pairs of authors over time.
基金This work is supported by the Programs for the Young Talents of National Science Library,Chinese Academy of Sciences(Grant No.2019QNGR003).
文摘Purpose:Research dynamics have long been a research interest.It is a macro perspective tool for discovering temporal research trends of a certain discipline or subject.A micro perspective of research dynamics,however,concerning a single researcher or a highly cited paper in terms of their citations and“citations of citations”(forward chaining)remains unexplored.Design/methodology/approach:In this paper,we use a cross-collection topic model to reveal the research dynamics of topic disappearance topic inheritance,and topic innovation in each generation of forward chaining.Findings:For highly cited work,scientific influence exists in indirect citations.Topic modeling can reveal how long this influence exists in forward chaining,as well as its influence.Research limitations:This paper measures scientific influence and indirect scientific influence only if the relevant words or phrases are borrowed or used in direct or indirect citations.Paraphrasing or semantically similar concept may be neglected in this research.Practical implications:This paper demonstrates that a scientific influence exists in indirect citations through its analysis of forward chaining.This can serve as an inspiration on how to adequately evaluate research influence.Originality:The main contributions of this paper are the following three aspects.First,besides research dynamics of topic inheritance and topic innovation,we model topic disappearance by using a cross-collection topic model.Second,we explore the length and character of the research impact through“citations of citations”content analysis.Finally,we analyze the research dynamics of artificial intelligence researcher Geoffrey Hinton’s publications and the topic dynamics of forward chaining.
基金The work was supported by the Science Committee of RA,in the frames of the research project No.20TTCG-5I013.
文摘Purpose:Nearly 122 scientific journals are currently being published in Armenia-of which only six are indexed by WoS and/or Scopus databases.The majority of the national journals are published in the Armenian language,solely possessing abstracts written in English,although there are also English-language and multi-language journals with articles not only in Armenian but also in other foreign languages.The aim of this article is to study the visibility of the(non-indexed)national Armenian journals in the WoS database through citation analysis.In consideration of the existence of a relevant Armenian“diaspora”in the world,this article also attempts to estimate its impact in terms of citation statistics.Design/methodology/approach:For this end,we have identified citations to the national/domestic Armenian journals in the WoS database in comparison with the share of citations received from“diaspora”researchers(researchers of Armenian origin born in foreign countries and those originally from Armenia who have emigrated to foreign countries).Findings:Among the 116 Armenian domestic journals analyzed(not indexed by WoS),only 47 were found to be cited in WoS.Of these journals,almost 12%are citations by“diaspora”researchers,most of which concern Social Science and Humanities journals.Research limitations:Although the surnames of Armenians end with-i(y)an,sometimes,the Diaspora Armenians,surnames are changed or modified or they are not ending with-i(y)an,in this case we may fail to identify them.Practical implications:This study can help to build new,more deep and comprehensive relations with scientific diasporas.Originality/value:This study offers a new understanding of multifaced research collaboration with scientific diasporas and their role in internationalization of domestic journals.
文摘The process of ranking scientific publications in dynamic citation networks plays a crucial rule in a variety of applications. Despite the availability of a number of ranking algorithms, most of them use common popularity metrics such as the citation count, h-index, and Impact Factor (IF). These adopted metrics cause a problem of bias in favor of older publications that took enough time to collect as many citations as possible. This paper focuses on solving the problem of bias by proposing a new ranking algorithm based on the PageRank (PR) algorithm;it is one of the main page ranking algorithms being widely used. The developed algorithm considers a newly suggested metric called the Citation Average rate of Change (CAC). Time information such as publication date and the citation occurrence’s time are used along with citation data to calculate the new metric. The proposed ranking algorithm was tested on a dataset of scientific papers in the field of medical physics published in the Dimensions database from years 2005 to 2017. The experimental results have shown that the proposed ranking algorithm outperforms the PageRank algorithm in ranking scientific publications where 26 papers instead of only 14 were ranked among the top 100 papers of this dataset. In addition, there were no radical changes or unreasonable jump in the ranking process, i.e., the correlation rate between the results of the proposed ranking method and the original PageRank algorithm was 92% based on the Spearman correlation coefficient.
基金National Natural Science Foundation of China Grant No.71673131Jiangsu Key Laboratory Fundsupport from the International Joint Informatics Laboratory operated cooperatively by the University of Illinois at Urbana-Champaign,USA and Nanjing University,China。
文摘Purpose:Using the metaphor of"unicorn,"we identify the scientific papers and technical patents characterized by the informetric feature of very high citations in the first ten years after publishing,which may provide a new pattern to understand very high impact works in science and technology.Design/methodology/approach:When we set CT as the total citations of papers or patents in the first ten years after publication,with CT≥5,000 for scientific"unicorn"and CT≥500 for technical"unicorn,"we have an absolute standard for identifying scientific and technical"unicorn"publications.Findings:We identify 165 scientific"unicorns"in 14,301,875 WoS papers and 224 technical"unicorns"in 13,728,950 DII patents during 2001–2012.About 50%of"unicorns"belong to biomedicine,in which selected cases are individually discussed.The rare"unicorns"increase following linear model,the fitting data show 95%confidence with the RMSE of scientific"unicorn"is 0.2127 while the RMSE of technical"unicorn"is 0.0923.Research limitations:A"unicorn"is a pure quantitative consideration without concerning its quality,and"potential unicorns"as CT≤5,000 for papers and CT≤500 for patents are left in future studies.Practical implications:Scientific and technical"unicorns"provide a new pattern to understand high-impact works in science and technology.The"unicorn"pattern supplies a concise approach to identify very high-impact scientific papers and technical patents.Originality/value:The"unicorn"pattern supplies a concise approach to identify very high impact scientific papers and technical patents.
文摘文章以Web of Science中收录的文献数据为分析对象,以计算机科学领域为例,验证国际合作是否能提高科学研究的影响力。为了检验国家数量与被引频次之间的相关性,开展了相关性分析和比较分析,并且分析了合作网络以了解各个国家所发挥的不同作用和影响。结果表明,国际合作论文的被引频次总体上高于国内作者的论文,但国家数量与被引频次之间仅存在弱相关关系。我国在2007—2009年期间共与65个国家开展了合作研究,其中19个国家在提高平均被引频次方面发挥了重要作用。
文摘医学信息学具有显著的学科交叉特性,大量学者采用定性或定量方法对医学信息学的学科内涵、领域特点、发展路径、研究前沿和发展趋势、现存问题等进行了深入的研究,但对该学科的跨学科特性进行系统研究相对较少。基于Web of science文献及学科类别数据,运用文献计量和知识图谱可视化技术,从多维角度较深入地揭示了医学信息学的学科交叉发展态势,旨在为促进医学信息学学科研究的发展提供参考。
