Improving nonlethal targeting: a social network analysis method for military planners
Outstanding Thesis === Approved for public release; distribution is unlimited === Nonlethal strategies are an essential part in the military targeting process to defeat and disrupt terrorist and insurgent networks. The majority of nonlethal options of military power come through Information Operatio...
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Monterey, California. Naval Postgraduate School
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ndltd-nps.edu-oai-calhoun.nps.edu-10945-278002015-05-06T03:58:38Z Improving nonlethal targeting: a social network analysis method for military planners Brown, Jason C. Roberts, Nancy Everton, Sean Defense Analysis Outstanding Thesis Approved for public release; distribution is unlimited Nonlethal strategies are an essential part in the military targeting process to defeat and disrupt terrorist and insurgent networks. The majority of nonlethal options of military power come through Information Operations, including the use of deception. This thesis explores how a deception plan against a terrorist network can be informed and prepared using social network analysis methods. Selecting targets that fragment the network becomes the object of the deception, whereas the actual targets of deception are individuals who are connected to these fragmentation nodes. A simulation of how information diffuses through the network helps identify how rapidly and how far a misinformation message might spread. Social network analysis also shows where intelligence collection might be incorporated to provide feedback about the success of message dissemination and the deception effort. 2013-02-15T23:13:23Z 2013-02-15T23:13:23Z 2012-12 Thesis http://hdl.handle.net/10945/27800 This publication is a work of the U.S. Government as defined
in Title 17, United States Code, Section 101. As such, it is in the
public domain, and under the provisions of Title 17, United States
Code, Section 105, is not copyrighted in the U.S. Monterey, California. Naval Postgraduate School |
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description |
Outstanding Thesis === Approved for public release; distribution is unlimited === Nonlethal strategies are an essential part in the military targeting process to defeat and disrupt terrorist and insurgent networks. The majority of nonlethal options of military power come through Information Operations, including the use of deception. This thesis explores how a deception plan against a terrorist network can be informed and prepared using social network analysis methods. Selecting targets that fragment the network becomes the object of the deception, whereas the actual targets of deception are individuals who are connected to these fragmentation nodes. A simulation of how information diffuses through the network helps identify how rapidly and how far a misinformation message might spread. Social network analysis also shows where intelligence collection might be incorporated to provide feedback about the success of message dissemination and the deception effort. |
author2 |
Roberts, Nancy |
author_facet |
Roberts, Nancy Brown, Jason C. |
author |
Brown, Jason C. |
spellingShingle |
Brown, Jason C. Improving nonlethal targeting: a social network analysis method for military planners |
author_sort |
Brown, Jason C. |
title |
Improving nonlethal targeting: a social network analysis method for military planners |
title_short |
Improving nonlethal targeting: a social network analysis method for military planners |
title_full |
Improving nonlethal targeting: a social network analysis method for military planners |
title_fullStr |
Improving nonlethal targeting: a social network analysis method for military planners |
title_full_unstemmed |
Improving nonlethal targeting: a social network analysis method for military planners |
title_sort |
improving nonlethal targeting: a social network analysis method for military planners |
publisher |
Monterey, California. Naval Postgraduate School |
publishDate |
2013 |
url |
http://hdl.handle.net/10945/27800 |
work_keys_str_mv |
AT brownjasonc improvingnonlethaltargetingasocialnetworkanalysismethodformilitaryplanners |
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1716803251620282368 |