Bibliometric study of social network analysis literature

Purpose The purpose of this paper is to use bibliometric analysis to identify the current state of the academic literature regarding social network analysis (SNA) and analyze its knowledge base such as research authors, research countries, document type, keyword analysis and subject areas. Design/me...

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Veröffentlicht in:	Library hi tech Jg. 38; H. 2; S. 420 - 433
Hauptverfasser:	Su, Yu-Sheng, Lin, Chien-Linag, Chen, Shih-Yeh, Lai, Chin-Feng
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Bradford Emerald Publishing Limited 15.06.2020 Emerald Group Publishing Limited
Schlagworte:	Academic discourse Analysis Author productivity Behavior Bibliometrics Citation indexes Citations Communication Computer mediated communication Computer science Computers Cooperation Distribution Electronic publishing Information literacy Information technology International cooperation Interpersonal communication Knowledge base Knowledge bases (artificial intelligence) Law Literary criticism Literature Network analysis Productivity Productivity measurement Research methodology Researchers Science Social network analysis Social networks Social sciences Telecommunications Writers North America Taiwan Bradford’s law Lotka’s law Social network analysis Literature Social sciences Bibliometrics
ISSN:	0737-8831, 2054-166X
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Abstract	Purpose The purpose of this paper is to use bibliometric analysis to identify the current state of the academic literature regarding social network analysis (SNA) and analyze its knowledge base such as research authors, research countries, document type, keyword analysis and subject areas. Design/methodology/approach Bibliometric analysis is used and furthermore, Lotka’s and Bradford’s law is applied to perform author productivity analyses in this field during 1999 and 2018, respectively, in turn, discovering historical vein and research tendency in the future. Findings It appears that the research on SNA has been very popular and still in the highly mature period. So far, the USA takes the lead among the published paper. The top 2 subject areas are “Computer Science” and “Business Economics.” The primary journal that SNA articles were published is Computers in Human Behavior. SNA has been related to many research areas, such as “Social network analysis,” “Computer-mediated communication,” “Online learning,” “Social Network” and “Community of inquiry.” Finally, Kolmogorov–Smirnov (K-S) test proved that the frequency indexes of author productivity distribution certainly followed Lotka’s law. Research limitations/implications First, the productivity distribution may inform researchers and scholars of current issues and development of SNA. Second, the study proposed a theoretical model, based on Lotka’s law, for author productivity analysis of SNA, which can serve as reference for different areas of study in the evaluation of author productivity models. Also, in order to allow researchers to gain in-depth insights, this study aimed to report the most published institutions and keep track of the growth and trend of author productivity, by which scholars in related fields are provided with more opportunities for academic communication and technological cooperation. Originality/value This research on the productivity distribution of SNA may inform researchers and scholars of current issues and development of SNA. The findings report the major publication outlets and related discussion issues about SNA. Such information would be valuable for related authors, who are writing the manuscript on SNA, and also for practitioners, who may be interested in applying the theory or ideas of SNA.
AbstractList	PurposeThe purpose of this paper is to use bibliometric analysis to identify the current state of the academic literature regarding social network analysis (SNA) and analyze its knowledge base such as research authors, research countries, document type, keyword analysis and subject areas.Design/methodology/approachBibliometric analysis is used and furthermore, Lotka’s and Bradford’s law is applied to perform author productivity analyses in this field during 1999 and 2018, respectively, in turn, discovering historical vein and research tendency in the future.FindingsIt appears that the research on SNA has been very popular and still in the highly mature period. So far, the USA takes the lead among the published paper. The top 2 subject areas are “Computer Science” and “Business Economics.” The primary journal that SNA articles were published is Computers in Human Behavior. SNA has been related to many research areas, such as “Social network analysis,” “Computer-mediated communication,” “Online learning,” “Social Network” and “Community of inquiry.” Finally, Kolmogorov–Smirnov (K-S) test proved that the frequency indexes of author productivity distribution certainly followed Lotka’s law.Research limitations/implicationsFirst, the productivity distribution may inform researchers and scholars of current issues and development of SNA. Second, the study proposed a theoretical model, based on Lotka’s law, for author productivity analysis of SNA, which can serve as reference for different areas of study in the evaluation of author productivity models. Also, in order to allow researchers to gain in-depth insights, this study aimed to report the most published institutions and keep track of the growth and trend of author productivity, by which scholars in related fields are provided with more opportunities for academic communication and technological cooperation.Originality/valueThis research on the productivity distribution of SNA may inform researchers and scholars of current issues and development of SNA. The findings report the major publication outlets and related discussion issues about SNA. Such information would be valuable for related authors, who are writing the manuscript on SNA, and also for practitioners, who may be interested in applying the theory or ideas of SNA. Purpose The purpose of this paper is to use bibliometric analysis to identify the current state of the academic literature regarding social network analysis (SNA) and analyze its knowledge base such as research authors, research countries, document type, keyword analysis and subject areas. Design/methodology/approach Bibliometric analysis is used and furthermore, Lotka’s and Bradford’s law is applied to perform author productivity analyses in this field during 1999 and 2018, respectively, in turn, discovering historical vein and research tendency in the future. Findings It appears that the research on SNA has been very popular and still in the highly mature period. So far, the USA takes the lead among the published paper. The top 2 subject areas are “Computer Science” and “Business Economics.” The primary journal that SNA articles were published is Computers in Human Behavior. SNA has been related to many research areas, such as “Social network analysis,” “Computer-mediated communication,” “Online learning,” “Social Network” and “Community of inquiry.” Finally, Kolmogorov–Smirnov (K-S) test proved that the frequency indexes of author productivity distribution certainly followed Lotka’s law. Research limitations/implications First, the productivity distribution may inform researchers and scholars of current issues and development of SNA. Second, the study proposed a theoretical model, based on Lotka’s law, for author productivity analysis of SNA, which can serve as reference for different areas of study in the evaluation of author productivity models. Also, in order to allow researchers to gain in-depth insights, this study aimed to report the most published institutions and keep track of the growth and trend of author productivity, by which scholars in related fields are provided with more opportunities for academic communication and technological cooperation. Originality/value This research on the productivity distribution of SNA may inform researchers and scholars of current issues and development of SNA. The findings report the major publication outlets and related discussion issues about SNA. Such information would be valuable for related authors, who are writing the manuscript on SNA, and also for practitioners, who may be interested in applying the theory or ideas of SNA.
Author	Lin, Chien-Linag Chen, Shih-Yeh Lai, Chin-Feng Su, Yu-Sheng
Author_xml	– sequence: 1 givenname: Yu-Sheng surname: Su fullname: Su, Yu-Sheng email: ntoucsiesu@mail.ntou.edu.tw – sequence: 2 givenname: Chien-Linag surname: Lin fullname: Lin, Chien-Linag email: lin.chienliang@gmail.com – sequence: 3 givenname: Shih-Yeh surname: Chen fullname: Chen, Shih-Yeh email: sychen@nttu.edu.tw – sequence: 4 givenname: Chin-Feng surname: Lai fullname: Lai, Chin-Feng email: cinfon@ieee.org
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Keywords	Bradford’s law Lotka’s law Social network analysis Literature Social sciences Bibliometrics
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Snippet	Purpose The purpose of this paper is to use bibliometric analysis to identify the current state of the academic literature regarding social network analysis... PurposeThe purpose of this paper is to use bibliometric analysis to identify the current state of the academic literature regarding social network analysis...
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Title	Bibliometric study of social network analysis literature
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