Friday, April 25, 2014

Spring Directed Field Work Week 4

This week I slammed and got through the other five chapters of structured analytical techniques.  I again highlighted techniques I felt were pertinent to my mentor’s needs of assessing social media data.

Chapter 8. Cause and Effect

  • 8.1 Key Assumptions Check
  • 8.2 Structured Analogies
  • 8.3 Role Playing
  • 8.4 Red Hat Analysis
  • 8.5 Outside-In Thinking
  • 8.6 Policy Outcomes Forecasting Model
  • 8.7 Prediction Markets


Chapter 9. Challenge Analysis

  • 9.1 Premortem Analysis
  • 9.2 Structured Self-Critique
  • 9.3 What If? Analysis
  • 9.4 High Impact/Low Probability Analysis
  • 9.5 Devil’s Advocate
  • 9.6 Red Team Analysis
  • 9.7 Delphi Method


Chapter 10. Conflict Management

  • 10.1 Adversarial Collaboration
  • 10.2 Structured Debate

Chapter 11. Decision Support

  • 11.1 Complexity Manager
  • 11.2 Decision Matrix
  • 11.3 Force Field Analysis
  • 11.4 Pros-Cons-Faults-Fixes
  • 11.5 SWOT Analysis


Chapter 12. Guide to Collaboration

  • 12.1 Social Networks and Analytic Teams
  • 12.2 Dividing the Work
  • 12.3 Common Pitfalls with Small Groups
  • 12.4 Benefiting from Diversity
  • 12.5 Advocacy vs Objective Inquiry
  • 12.6 Leadership and Training

At the end of the week, I sat down with my mentor and went through the extremely large slide deck as quickly as possible and told him techniques I highlighted were meant for the problem they were looking at originally.  He was really happy with my slides but would like me to focus on social media techniques in general that can be used as a streamlined process.  So I will be going through all of the slides again and inputting information on all of the techniques and we will go through each one, one by one next week with a few scientists in the visual analytics group and get their input as well.  So he asked me to set up this meeting and add the additional information for next week.

Friday, April 18, 2014

Spring Directed Field Work Week 3

I continued with the Powerpoint Slide deck from the chapters of the “Stuctured Analytic Techniques”.  Chapters 4-12 give the full description of the analytical techniques broken down into individual sections.  There are 52 techniques in total.  The chapter gives a brief overview of the individual techniques then the sections talk more in depth about each one.  The chapters and sections I completed for the week are the following:

Chapter 4. Decomposition and Visualization

  • 4.1 Getting started checklist
  • 4.2 Customer Checklist
  • 4.3 Issue Redefinition
  • 4.4 Chronologies and Timelines
  • 4.5 Sorting
  • 4.6 Ranking, Scoring, and Prioritizing
  • 4.7 Matrices
  • 4.8 Network Analysis
  • 4.9 Mind Maps and Concept Maps
  • 4.10 Process Maps and Gantt Charts

Chapter 5. Idea Generation

  • 5.1 Structured Brainstorming
  • 5.2 Virtual Brainstorming
  • 5.3 Nominal Group Technique
  • 5.4 Starbursting
  • 5.5 Cross-Impact Matrix
  • 5.6 Morphological Analysis
  • 5.7 Quadrant Crunching

Chapter 6. Scenarios and Indicators

  • 6.1 Scenarios Analysis
  • 6.2 Indicators
  • 6.3 Indicators Validator

Chapter 7. Hypothesis Generation and Testing

  • 7.1 Hypothesis Generation
  • 7.2 Diagnostic Reasoning
  • 7.3 Analysis of Competing Hypotheses
  • 7.4 Argument Mapping
  • 7.5 Deception Detection

In each of the individual sections it breaks down each with the following criteria:

  • Technique Name
  • Description
  • When to Use It
  • Value Added
  • The Method
  • Relationship to Other Techniques
  • Origins of This Technique

If I found the technique to be of value to the analysis of social media I would flag the technique and do a full description of it on the Powerpoint Slides.  Lots of chapters and sections to get through!

Friday, April 11, 2014

Spring Directed Field Work Week 2

One of the deliverables for this research will be a Powerpoint Slide deck outlining descriptions of each of the analytical techniques described in Heuer’s 2011’s textbook “Structured Analytic Techniques for Intelligence Analysis”.  The slides will also describe how the techniques can be used with social media data. 

I began the slide deck by reading about the role of an intelligence analyst and the purpose of their job

Intelligence Analysts

Analysis

Structured Analytics  

Before looking at social media data, understanding the taxonomy of data is also an essential component to problem.

Taxonomy

Taxonomy2 

In addition I met with a colleague to discuss how Twitter data is extracted from a  search and what programming tools and techniques he uses to analyze the data.  He mentioned using the R programming language, Yahoo! Pipeline, 140 Dev for free sourcecode APIs, D3, CRAN and WEKA.  Quite a bit of metadata can be extracted from Twitter data such as: user ID, the text from the tweet, re-tweets, IP address, hashtags, mentions, date/time stamp, device, and even URLs.  We discussed what visualization tools he is familiar with using.  In my previous Directed Field Work in the Summer of 2013, I had used a couple of in-house PNNL visualization tools (IN-SPIRE and Starlight), IBM’s Analyst Notebook, and Tableau Software to visualize social media data.  At the time just visualizing the data is one thing, extracting out interesting relationships, trends and discovering a story from the data is where analysis comes into play.

Friday, April 4, 2014

Spring Directed Field Work Week 1

This first week of Spring 2014’s Directed Field Work was about getting to know my mentor, the previous work he has done, goals for my learning experience and filling out the Learning Outcomes Agreement form.  I will be working with my mentor fifteen hours a week for the next ten weeks.  My mentor is passionate about utilizing social media and discovering trends and intersections with health security and is a huge proponent of health advocacy.  His group had previously done research on utilizing social media to detect the progression or emergence of the Middle East Respiratory Syndrome Coronavirus (MERS-CoV) and would like me to help him out in looking at different techniques or methods to analyze the data.

There are three goals for this project:

  • Become familiar with the types of structured analytical techniques and conceptual models to be used with social media data
  • How are people analyzing social media content for intelligence analysis and decision making or support
  • Cross correlate current techniques and possibility of creating a new analytical technique to analyze social media data

The two textbooks I will be looking at throughout this project include the following:

Structured Analytic Techniques for Intelligence Analysis by Richard Heuer and Randolph Pherson

image

 

Intelligence Analysis: How to Think in Complex Environments by Wayne Michael Hall and Gary Citrenbaum

Intelligence Analysis

Initially my mentor would like me to become familiar with the sections of the textbooks, research done using he slide deck, learn about basic and advanced searching in social media tools and look at sample scenarios.