Discovering Scientific Collaboration Activities using Social Network Analysis. A Case Study: Faculty of Computer Science Universitas Indonesia

Abstract

Research collaboration is needed to accomplish the University’s targets: improve quality, collaboration, and partnerships in research. Identifying research collaboration is required as located research elements to facilitate research and encourage interdisciplinary collaboration. This research is aimed to discover scientific collaboration activities in the computer science domain on the Faculty of Computer Science, Universitas Indonesia. Using metadata as research data is a solution for embedded knowledge in unstructured documents. The information was collected online publications metadata from Scopus that published from 1988 to 2018. We used social network analysis (SNA) to map and measure scientific actors’ relationships to understand collaboration activities from various views of different elements and to build the author’s research profile. Based on the data, we can get information about the expertise of institution researchers and their relationships with other collaborators. Moreover, we can get information about the most popular actor, influenced actors, the bridge actors based on the relation map. The methodology in this research can be used to discover knowledge in other research domains and organizations, and the analysis of this research can be used for research management.