tgbn_trade — International agricultural trade shares (tgbn-trade, TGB, 1986-2016)

Description

Yearly directed networks of the international trade in agricultural products between the nations of the United Nations from 1986 to 2016, from the tgbn-trade dataset of the Temporal Graph Benchmark (TGB), based on the data of MacDonald et al. (2015), compiled from FAOSTAT. Each node is a nation, and an edge from nation A to nation B in a year means that A traded agricultural products with B in that year (the edges of all years form a single network, with the year as an edge property). The weight of an edge is the share of the trade of A that goes to B in that year, i.e. the trade values (the sum over all agricultural products) normalized by TGB so that the weights of the edges from each nation in each year sum to one; the trade values themselves are not included in the data.

The network has the following properties:

name: the name of the nation.
Edge year: the year of the trade.
Edge share: the share of the trade of the source nation with the target nation in that year.

Tags

Economic Trade Weighted Multigraph Timestamps Metadata

Citation

S. Huang, F. Poursafaei, J. Danovitch, M. Fey, W. Hu, E. Rossi, J. Leskovec, M. Bronstein, G. Rabusseau, R. Rabbany, "Temporal Graph Benchmark for Machine Learning on Temporal Graphs." Advances in Neural Information Processing Systems 36 (Datasets and Benchmarks Track) (2023) 10.48550/arXiv.2307.01026 Sci-Hub
G. K. MacDonald, K. A. Brauman, S. Sun, K. M. Carlson, E. S. Cassidy, J. S. Gerber, P. C. West, "Rethinking Agricultural Trade Relationships in an Era of Globalization." BioScience 65(3), 275-289 (2015) 10.1093/biosci/biu225 Sci-Hub

Upstream URL OK

https://tgb.complexdatalab.com/docs/nodeprop/
https://github.com/shenyangHuang/TGB

Upstream license

MIT

Networks

Tip: hover over a column header for a description.

Column legend

$\left<k\right>$: Mean degree
$\sigma_k$: Standard deviation of the degrees
$\lambda_h$: Largest eigenvalue of the Hashimoto (non-backtracking) matrix
$\tau$: Random walk mixing time
$r$: Degree assortativity
$c$: Global clustering coefficient
$\oslash$: (Pseudo-) diameter
$S$: Relative size of the largest component
NPs: Node properties
EPs: Edge properties

Name	Nodes	Edges	$\left<k\right>$	$\sigma_k$	$\lambda_h$	$\tau$	$r$	$c$	$\oslash$	$S$	Kind	Mode	NPs	EPs	gt	GraphML	GML	csv
tgbn_trade	255	468,245	1836.25	2996.83	180.04	0.67	-0.31	0.91	3	1.00	Directed	Unipartite	name	year share	3.2 MiB	5.5 MiB	5.4 MiB	5.4 MiB

Ridiculograms^*

^* These are automatically generated force-directed visualizations, and can be quite meaningless for networks both big and small. They should not be taken seriously as sources of scientific insight. See here for a discussion.