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. 2018 Aug 24;3(1):36. doi: 10.1007/s41109-018-0092-1

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© The Author(s) 2018

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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Fig. 5 — Fragmentation results of the federal criminal intelligence network represented by the relative size of the largest connected component, G, as a function of the percentage of nodes/edges removed, q, according to procedures based on different measurements: a, node removal by Degree (HD - black squares), Betweenness (HB - blue triangles), and Modular (MBA - red circles); b, edge removal by Betweenness (eHB - black squares), Betweenness Adaptive (eHBA - blue triangles), and Modular (eMBA - red circles); c, node removal by Degree Adaptive (HDA - black squares), Collective Influence (CI - lower green triangles), Betweenness Adaptive (HBA - blue triangles), and Modular (MBA - red circles)