Accession Number:

AD1065513

Title:

Crowd-Based Techniques to Improve Intelligence Analysis

Descriptive Note:

Technical Report

Corporate Author:

Naval Postgraduate School Monterey United States

Personal Author(s):

Report Date:

2018-09-01

Pagination or Media Count:

153.0

Abstract:

The essential nature of the homeland security enterprise involves making consequential and complex policy decisions under uncertainty. The inputs that policy makers use in making these decisions are facts, analyses, and predictions which can fit a definition of intelligenceall of which are subject to significant uncertainty. This thesis seeks to improve analysis by developing a crowd-based analytic methodology to address the problem of intelligence analysis while accounting for, and taking advantage of, the unique characteristics of the intelligence analysis process and the U.S. Intelligence Community culture itself. The thesiss proposed methodology applies learning regarding crowdsourcing and prediction marketsbased forecasting in a new contextthat of intelligence analysis and the Intelligence Community. If the Intelligence Community implements the crowd-based analytic proposed methodology, which has achieved results in other contexts, it should improve its predictions of real-world events.

Subject Categories:

  • Military Intelligence
  • Information Science

Distribution Statement:

APPROVED FOR PUBLIC RELEASE