Bibliometric study of social network analysis literature

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.

Citation

Su, Y.-S., Lin, C.-L., Chen, S.-Y. and Lai, C.-F. (2020), "Bibliometric study of social network analysis literature", Library Hi Tech, Vol. 38 No. 2, pp. 420-433. https://doi.org/10.1108/LHT-01-2019-0028