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Topology Analysis of International Networks Based on Debates in the United Nations
[article]
2017
arXiv
pre-print
In complex, high dimensional and unstructured data it is often difficult to extract meaningful patterns. This is especially the case when dealing with textual data. Recent studies in machine learning, information theory and network science have developed several novel instruments to extract the semantics of unstructured data, and harness it to build a network of relations. Such approaches serve as an efficient tool for dimensionality reduction and pattern detection. This paper applies semantic
arXiv:1707.09491v1
fatcat:p4aeif7slnfuznezshvx3rmjji