Who is who in Big Social Data?: A Bibliographic Network Analysis Study

Abstract

The aim of the study is to investigate who are advancing the knowledge on Big Social Data and the related concept of Social Big Data, ‘who’ are these people citing and building their work on, and what are the topics and outlets where the discussion takes place. For that purpose, data was extracted from Thomson Reuters Web of Science with the search term “Big Social Data” and “Social Big Data” spanning the years from 2012 to 2016. The search resulted in 58 articles in 39 different outlets. In order to go into the depth of Big Social Data and Social Big Data, co-author bibliographic<br/>network analysis was performed on the extracted data. The co-author network analysis revealed 149 nodes (authors), and 308 edges (co-authoring relationships) between the authors. Betweenness centrality were calculated for the nodes to<br/>demonstrate who are the central authorities and their domain on the topic of Big Social Data and Social Big Data. The visualisation based on co-author network analysis provides insight into the possible clusters of authors in the topics of Big<br/>Social Data and Social Big Data. Co-citation analysis was performed for the combined network of Big Social Data and Social Big Data authors. This study was carried out using Ostinato process model for visual network analysis. The findings of the<br/>study provide insights on the leading authorities (authors) advancing the knowledge in Big Social Data. From the community of Big Social Data three authorative clusters were identified, one with authors located in Singapore and Scotland, another with authors located in Denmark, and third based in London, England. The Social Big Data communities were mainly located in Asia, with two authorative clusters, one located in Japan, and another with authors located in South-Korea and Spain. The topic modelling uncovered that the themes discussed in Big Social Data and Social Big Data<br/>communities were fairly similar, dealing with analysis of social media data in various ways. Most commonly the focus was on Twitter or Facebook data analysis. Further, the bibliometric analysis provides an indication for potential outlets (Journals and Conferences) for Big Social Data and Social Big Data themed articles, as well as, their impact on the field.