Categorization of survey text utilizing natural language processing and demographic filtering
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Authors
Cairoli, Christine M.
Subjects
Navy retention
survey comments
comment labeling
text analysis
natural language processing
survey comments
comment labeling
text analysis
natural language processing
Advisors
Whitaker, Lyn R.
Date of Issue
2017-09
Date
Sep-17
Publisher
Monterey, California: Naval Postgraduate School
Language
Abstract
Thousands of Navy survey free text comments are overlooked every year because reading and interpreting comments is expensive, time consuming, and subjective. Valuable information from these comments is not being utilized to make important Navy decisions. We provide a new procedure to automate the identification of primary topics in short, jargon laced, topic based survey comments by applying a label to each comment and then using those labels to bin comments into operationally meaningful categories. We apply this method to the Navy Retention Survey to provide the Chief of Naval Personnel with an objective analysis of the questions Why are sailors leaving? and What will make sailors stay on active duty? Furthermore, we introduce an implementation of this method using the Demographic Analysis of Responses Tool for Surveys (DARTS), which allows us to filter comment bins using the over 100 demographic and military status elements associated with each sailor. By targeting critically undermanned specialties, the reports generated with this tool provide quantifiable results that allow retention policy makers the ability to review, modify, and create relevant incentives to retain critically talented sailors to meet fiscal year end strength and operational requirements.
Type
Thesis
Description
Series/Report No
Department
Operations Research (OR)
Organization
Identifiers
NPS Report Number
Sponsors
Funder
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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.