Using Social Network Analysis to Study Business Partnerships

Abstract

Social network analysis is gaining increased interest due to the expansion of social media and networking websites. Network analysis also significantly contributes to the biomedical sector in analysing protein networks and interactions. This paper proposes a new domain for network analysis of analysing business partnerships as an interesting economic aspect. Datasets of business partners featuring trade licenses created in 2015, 2016, and 2017 are transformed into graph datasets with nodes representing business partners, links representing a relationship between two partners, and a link’s weight representing the number of trade licenses shared between the two connected partners. The resulting weighted undirected network is analysed using community detection algorithms. Characteristics of the top seven communities discovered from the 2015 data are discussed for which common social network motifs are captured. The behaviour of the seven discovered clusters are also analysed over the subsequent two years for deeper insights into business partnerships behaviours.