Dynamic network analysis of online interactive platform

The widespread use of online interactive platforms including social networking applications, community support applications draw the attention of academics and businesses. The basic trust of this research is that the very nature of these platforms can be best described as a network of entangled interactions. We agree with scholars that these platforms and features necessitate the call for theory of network as a novel approach to better understand their underpinnings. We examine one of the leading online interactive health networks in Europe. We demonstrate that the interactive platform examined exhibits essential structural properties that characterize most real networks. In particular, we focus on the largest connected component, so-called a giant component (GC), to better understand network formation. Dynamic network analysis helps us to observe how the GC has evolved over time and to identify a particular pattern towards emerging a GC. We suggest that the network measures examined for the platform should be considered as novel and complementary metrics to those used in conventional web and social analytics. We argue that various stages of GC development can be a promising indicator of the strength and endurance of the interactions on the platform. Platform managers may take into account basic stages of the emergence of the GC to determine varying degrees of product attractiveness.