Publication:
Automated psychological categorization via linguistic processing system

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Authors
Sutter, Christopher M.
Eramo, Mark D.
Subjects
Advisors
Buettner, Raymond R.
Kamel, Magdi N.
Date of Issue
2004-09
Date
Publisher
Monterey, California. Naval Postgraduate School
Language
Abstract
Influencing one's adversary has always been an objective in warfare. However, to date the majority of influence operations have been geared toward the masses or to very small numbers of individuals. Although marginally effective, this approach is inadequate with respect to larger numbers of high value targets and to specific subsets of the population. Limited human resources have prevented a more tailored approach, which would focus on segmentation, because individual targeting demands significant time from psychological analysts. This research examined whether or not Information Technology (IT) tools, specializing in text mining, are robust enough to automate the categorization/segmentation of individual profiles for the purpose of psychological operations (PSYOP). Research indicated that only a handful of software applications claimed to provide adequate functionality to perform these tasks. Text mining via neural networks was determined to be the best approach given the constraints of the profile data and the desired output. Five software applications were tested and evaluated for their ability to reproduce the results of a social psychologist. Through statistical analysis, it was concluded that the tested applications are not currently mature enough to produce accurate results that would enable automated segmentation of individual profiles based on supervised linguistic processing.
Type
Thesis
Description
Series/Report No
Department
Information Sciences (IS)
Organization
Naval Postgraduate School (U.S.).
Identifiers
NPS Report Number
Sponsors
Funder
Format
xiv, 123 p. : ill. (some col.) ;
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
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