An Analytic Framework for the War of Ideas

Abstract

One of the objectives listed in the 2003 "National Strategy for Combating Terrorism" is to win the "War of Ideas." This thesis seeks to place an analytic framework around this war. The goal is to create a methodology for considering alternatives and some concrete metrics with which to compare courses of action. The fundamental assumption is that one-to-one (i.e., interpersonal) communication is the most important in spreading ideas. The tools used are deterministic and stochastic models that were originally developed for infectious diseases and rumor propagation. The fundamental idea is that when two people in the population connect (e.g., through direct contact, phone, or e-mail, etc.), the ideology may be spread. These models are similar to traditional epidemic models. Many extensions to the idea of the spread of ideology as disease are possible and some are explored in this work. The author extends previous work by placing ideology in a greater social context. He introduces two diametrically opposed ideas and models their flow. He refers to the proponents of these ideas as the "supporters" and "contrarians." He considers the case in which both the supporters and contrarians openly vie for a greater share of support from the public. This case is similar to a political campaign in the United States without the influence of media. He also considers the case in which the supporters are able to openly propagate their message, but the contrarians only interact when supporters try to convert them. He believes this is the case where there is a small but dedicated extremist subpopulation. The results show that under the model assumptions, a relatively small number of contrarians are required to overcome a large increase in the supporters.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2006
Accession Number
ADA457312

Entities

People

  • Harrison C. Schramm

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Biomedical
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Applied Mathematics
  • Attrition
  • California
  • Computational Science
  • Differential Equations
  • Equations
  • Infectious Diseases
  • Markov Chains
  • Mathematical Models
  • New York
  • Numerical Analysis
  • Operations Research
  • Probability
  • Random Variables
  • Stochastic Processes
  • United States

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Computational Modeling and Simulation
  • Political Violence and Terrorism Studies.