Citation and bibliographic coupling between authors in the field of social network analysis  

作　　者：Daria Maltseva Vladimir Batagelj 

机构地区：[1]National Research University Higher School of Economics,101000 Moscow,Russia [2]Institute of Mathematics,Physics and Mechanics,1000 Ljubljana,Slovenia [3]University of Primorska,Andrej MarušičInstitute,6000 Koper,Slovenia

出　　处：《Journal of Data and Information Science》2024年第4期110-154,共45页数据与情报科学学报（英文版）

基　　金：supported in part by the Slovenian Research Agency(VB,research program P1-0294);(VB,research project J5-2557);(VB,research project J5-4596);COST EU(VB,COST action CA21163(HiTEc);is prepared within the framework of the HSE University Basic Research Program.

摘　　要：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 charac

关 键 词：Development of scientific fields Social network analysis Bibliographic network Temporal network CITATION Bibliographic coupling 

分 类 号：G353.1[文化科学—情报学]