Social network analysis of global transshipment: a framework for discovering illegal fishing networks

Knowledge Discovery and Data Mining(2020)

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摘要
BSTRACTIllegal, Unreported and Unregulated fishing activities contribute to economic and environmental issues across the world. Research has been done to leverage technology in the combat against illegal fishing, and methods have been published to enable the use of technology-driven tactics by authorities in charge of maritime monitoring. A challenge in continuing to combat these activities is transshipment, a practice in which transport vessels are used to mask the origins of marine products. This paper proposes a framework to use transshipment encounters as a basis for understanding the criminal networks profiting from illegal fishing by generating a global network of transshipment. The use of a network structure to represent vessels and their relationships enables the use of formal methods derived from social network analysis to interpret the structures of the criminal organizations engaging in criminal fishing activities worldwide. A framework for generating and visualizing this global network is discussed, and strategies to detect criminal activity are proposed, such as the calculation of the criminal centrality metric. This framework utilizes social network analysis techniques on the domain of illegal fishing and can empower law enforcement agencies to investigate criminal fishing operations on a global scale.
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关键词
social network analysis and visualization,illegal fishing,transshipment,criminal networks
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