Multi-Attribute Community Detection in International Trade Network
نویسندگان
چکیده
Abstract Understanding the structure of communities in a network has great importance economic analysis. Communities are indeed characterized by specific properties, that different from those both individual nodes and whole network, they can affect various processes on network. In International Trade Network, community detection aims to search sets countries (or trade sectors) which have high intra-cluster connectivity low inter-cluster connectivity. general, exchanges among occur according preferential relationships ranging over sectors. this paper, we combine with topological indicators, such as centrality measures. As result, new weighted is constructed original one, weights determined taking into account all indicators multi-criteria approach. To solve resulting Clique Partitioning Problem find homogeneous group nations, use fast algorithm, based quick descents local optimal solution. The analysis allows cluster interconnections, power intensity trade, giving an important overview international patterns.
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ژورنال
عنوان ژورنال: Networks and Spatial Economics
سال: 2021
ISSN: ['1566-113X', '1572-9427']
DOI: https://doi.org/10.1007/s11067-021-09547-4