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

Abstract

Abstract 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.

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Papers that cite the same references — the relational fallback while embeddings are still backfilling.