Abstract
This paper presents a study of authors writing articles in the field of SNA and groups them by means of bibliographic network analysis. The dataset consists of works from the Web of Science database obtained by searching for “social network*”, works highly cited in the field, works published in the flagship SNA journals, and written by the most prolific authors (70,000+ publications and 93,000+ authors), up to and including 2018. Using a two-mode network linking publications with authors, we constructed and analysed different types of collaboration networks among authors. We used the temporal quantities approach to trace the development of these networks through time. The results show that most articles are written by 2 or 3 authors. The number of single authored papers has dropped significantly since the 1980s—from 70% to about 10%. The analysis of three types of co-authorship networks allowed us to extract the groups of authors with the largest number of co-authored works and the highest collaborative input, and to calculate the indices of collaborativeness. We looked at the temporal properties of the most popular nodes. We faced the problem of “multiple personalities” of mostly Chinese and Korean authors, which could be overcome with the adoption of standardized author IDs by publishers and bibliographic databases.
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Acknowledgements
All computations were performed using the program for large network analysis and visualization Pajek (De Nooy et al., 2018) and Python code based on the library Nets (Batagelj, 2020a). Visualizations of distributions and temporal quantities were produced in R. We appreciate the help of David Connolly (Academic Writing Center, HSE University, Moscow) with the proofreading of the article.
Funding
This work is supported in part by the Slovenian Research Agency (research program P1-0294 and research projects J1-9187 and J5-2557), project COSTNET (COST Action CA15109), and prepared within the framework of the HSE University Basic Research Program.
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Maltseva, D., Batagelj, V. Collaboration between authors in the field of social network analysis. Scientometrics 127, 3437–3470 (2022). https://doi.org/10.1007/s11192-022-04364-z
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DOI: https://doi.org/10.1007/s11192-022-04364-z