1. Integrated Visual Analysis of Global Terrorism
Remco Chang
Charlotte Visualization Center
UNC Charlotte

2. GTD Data
It’s a large dataset. GTD has 59,603 incidents, with 119 attributes (dimensions) for each incident.
It covers almost all incidents happened from 1970 to 1997, across the whole world.
It contains mixed types of attribute --- Categorical and Numerical.
It also includes uncertain/unknown incidents.

3. Dimensional Relationships
Visual GTD Flow Chart
Entity Relationships
(Geo-temporal Vis)
Dimensional Relationships
(ParallelSets)
Entity Analysis
(Search By Example)

4. Five Flexible Entry Components
WHO – Terrorist Groups
Five Flexible Entry Components
What
WHERE~
WHEN

5. Enter System by single or multiple Selections
System will supply Specific Information
Drilldown to Original Info

6. Parallel Sets View Parallel Sets
Displays relationships among categorical dimensions
Shows intersections and distributions of categories

7. Parallel Sets View
Dynamic filtering on continuous dimensions can show more information
Here we see the large proportion of facility attacks and bombings in Latin America during the early 1980s

8. Analysis using Longest Common Sequence (LCS)
Two strings of data (each representing a series of events)
GATCCAGT
GTACACTGAG
Basic algorithm returns length of longest common subsequence: 6
Can return trace of subsequence if desired:
GTCCAG
Additional variations can take into account event gap penalties, time gap penalties, and exploration of shorter, or alternate, common subsequences

9. MDS Analysis by TargetType
Grouping using MDS in 2D
Each o represents a terrorist group
Groups form cluster according to naturally occurring trend sizes
Sharp divide between large clusters in right hemisphere
Left hemisphere contains many smaller clusters
MDS Analysis by TargetType

10. Integrated Terrorism Analysis
Multimedia
Real Time
Known Events
Visual GTD

11. Video Analysis Goals to describe trends in news content over time
to discover breaking news and hot topics over time
to trace conceptual development of news
to retrieve news of interests effectively
to collect evidences and test hypotheses for intelligent analysis
to compare group (such as different channels) differences in content
to associate news content with social events

12. Multimedia Analysis

13. Video Analysis Example
CNN Fox News MSNBC
News contains view points and opinions
Find local, regional, national, and international reports of the same event to get a complete picture

14. NVAC Collaborations Visual Analytics is the point of integration!!
PNNL – A. Sanfilippo (Content Analysis and Information Extraction of closed caption)
PNNL – W. Pike (Emotional state extraction from closed caption)
Penn State – A. MacEachren (Geographical analysis)
Georgia Tech – J. Stasko (Jigsaw, entity relationships)
Visual Analytics is the point of integration!!

15. Integrating Terrorism Data Analysis and News Analysis
Terrorism Databases
Terrorism Visual Analysis
Terrorism VA
Jigsaw
Stab/
TIBOR
Reasoning
Environment
NVAC
Framing,
Affective Analysis
Broadcast VA
News
Visual Analysis
Broadcast VA provides text stories. With help of our friends, we will analyze this content, then connect back to better news video analyses. Ultimately, this will provide a new dimension to terrorism analyses based on GTD and similar databases.
Different angles and also fuller stories (local for local news, etc.)
Reporters are trained to provide the essence of a story very clearly.
News Story Databases
Next: full, Web-based multimedia content