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Mapping Gray Maritime Networks Cover

Abstract

This research focused on the identification and tracking of subgroups of vessels of interest, owners, operators, ports, cargoes, and specific activities associated with artificial reef enhancement and construction in the South China Sea. Historical automated information system (AIS) tracks and current maritime databases were used to develop sociogram depictions of the gray (licit but only partially transparent) maritime network that connects these nodes (ships, events, organizations, ports, activities). Social network matrices were dynamically updated by open source databases to provide insights into real-time awareness and tracking for operational purposes.

The maritime network data set was populated by, and dynamically updated through, the integration of unclassified data using algorithms developed as part of the research. Longitudinal topographic metrics  –  average degree, average clustering coefficient, and centralization  –  were used to analyze the multi-mode (e.g., ship to ship, ship to owners/operators, owner/operators to owner/operators, ships to locations) relationships within the gray maritime network. Additionally, the network of ports and reefs in the area of operations was mapped and insights were gained by leveraging directed centrality measures  –  hubs and authorities  –  connecting them.

DOI: https://doi.org/10.21307/connections-2019-006 | Journal eISSN: 2816-4245 | Journal ISSN: 0226-1766
Language: English
Page range: 1 - 12
Published on: Oct 23, 2019
Published by: International Network for Social Network Analysis (INSNA)
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2019 Wayne Porter, Rob Schroeder, Chris Callaghan, Albert Barreto, Sam Bussell, Brian Young, Manuel Loewer, Daniel Funk, Janet von Eiff, published by International Network for Social Network Analysis (INSNA)
This work is licensed under the Creative Commons Attribution 4.0 License.