ABSTRACT
This chapter proposes to uncover clusters in a maritime flow network extracted from Lloyd's List where geographical information is available as well as the type of preferential commodities. The research determines the possible influence of geography and cargo specialization on the emergence of clusters in a maritime network. The maritime network is a multilayered system, as different fleet types have different logics of circulation that more or less overlap and connect via port nodes. The chapter further focuses on the application of stochastic block model (SBM) and random subgraph model (RSM) methods to a maritime flow network, extracted from the well-known Lloyd's List. Extensions of SBM include the mixed membership stochastic block model (MMSBM) and the overlapping stochastic block model (OSBM). They both allow a vertex to belong to multiple clusters at the same time. The RSM was proposed to analyze directed networks with typed edges for which a partition of the vertices is available.
