A time-evolving weighted-graph analysis of global petroleum exchange

Networks have become an influential part of our society. New social ties are being formed or existing ties are removed in social networks. Technological networks, such as the Internet and power grid are heavily relied upon to perform daily tasks, and biological networks inspire us to develop and optimize processes. Much of the existing studies consider networks as unweighted graphs, predominantly because of lack of data and tools. However, weights influence the importance of nodes or links in a network, and considering the weights is realistic in graph analysis. Orthogonal to the weighted graphs, the evolution of graphs can help us predict the future state of a network. In this paper, we study the evolution of global petroleum exchange as a weighted graph. We analyze 17 years of global petroleum imports and exports data between all counties with samples and show that the countries´ import and export increased. We also rank the most important countries according to important graph centrality metrics and our rankings vary based on the metric being used. The evolution of the global petroleum exchange graph represents that new ties between countries formed and the graph size increased.