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Assessing Instability in the Information Age: Managing Overwhelming Information with Simple Models Daniel T. Maxwell, Ph.D. Vice President Evidence Based.

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Presentation on theme: "Assessing Instability in the Information Age: Managing Overwhelming Information with Simple Models Daniel T. Maxwell, Ph.D. Vice President Evidence Based."— Presentation transcript:

1 Assessing Instability in the Information Age: Managing Overwhelming Information with Simple Models Daniel T. Maxwell, Ph.D. Vice President Evidence Based Research, Inc.

2 2 That Trust Thing Social Domain Interaction Language Trust Physical Domain Computers Phones Tools Cognitive Domain Knowledge Experience Beliefs Information Domain Data Input Formal Network Informal Network A Picture of Trust Related Concepts

3 3Overview Project Overview Project Overview Supplemental architecture Supplemental architecture The baseline model The baseline model Demonstrate the Model Demonstrate the Model Strengths and weaknesses Strengths and weaknesses

4 4 Project Goals Automatically and continuously harvest open source information to support analysisAutomatically and continuously harvest open source information to support analysis Automatically derive and generate event data for structured modelsAutomatically derive and generate event data for structured models Explore the utility of Bayesian Networks to identify instability / early warningExplore the utility of Bayesian Networks to identify instability / early warning

5 5 Documents Open Source All Source DB Parsing Linguistic Processor Linguistic Processor Extract / Transform KB Rule Development Rule Development High Resolution Data Stream DB Information Processing Architecture

6 6 Linguistic Processor Refines Data Event classification Textual data of interest

7 7 Instability indicators derived from: Scarborough, Grace. “Forecasting Political Instability in a Three-Year Period.” Baseline (Time 0) Bayes Net Model is currently initialized using nominal data Illustrative Value Only

8 8 Documents Open Source All Source DB Parsing Linguistic Processor Linguistic Processor Extract / Transform KB Rule Development Rule Development Bayesian Inference Model DB Instability Assessment Process Overview

9 9 Create Input Data for Bayes Network

10 10 Model Result at Time 1 Changes Probability of Instability

11 11 Sample Results Over Time Alert Desk Officer

12 12 Conclusions and Future Research Conclusions Conclusions Appears to effectively “trigger” areas of interestAppears to effectively “trigger” areas of interest Provides consistent and traceable results (Audit Trail)Provides consistent and traceable results (Audit Trail) Early indications of system scalability (Large Quantities of Data, Many Countries / Regions)Early indications of system scalability (Large Quantities of Data, Many Countries / Regions) Scoped to information sourcesScoped to information sources Future Research Future Research Larger data setLarger data set Adjudication of information quality (veracity, sensitivity, bias)Adjudication of information quality (veracity, sensitivity, bias) Instantiating Immature TheoryInstantiating Immature Theory


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