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- W4313372451 abstract "Kennedy, Sean Wish, Michael Smith, Philip Sherrell, James Shields, William Gera, RaluccaThis paper presents an accurate, scalable, time-dependent synthetic network model for the World Trade Web (WTW), whose nodes are the different countries that traded from 1996–2020. Using only an initial distribution of countries’ global Gross Domestic Product (GDP) as an input, our synthetic network model initializes weighted undirected edges corresponding to total trade between two countries using the presence of a hidden fitness variable dependent on GDP. The synthetic model simulates the creation and deletion of new and existing trade relationships aligned with real-world data. Our results show that this simulated network continues to faithfully approximate the data from WTW about 20 years after creation within a reasonable degree of accuracy." @default.
- W4313372451 created "2023-01-06" @default.
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- W4313372451 date "2022-01-01" @default.
- W4313372451 modified "2023-09-28" @default.
- W4313372451 title "Building a Reliable, Dynamic and Temporal Synthetic Model of the World Trade Web" @default.
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- W4313372451 doi "https://doi.org/10.1007/978-3-031-17658-6_6" @default.
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