1 Overview of Social Network Analysis Donna Nystrom Aerospace Data Mining Center...

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Overview of Social Network Analysis

Donna NystromAerospace Data Mining Center

[email protected](310)336-5303


Outline

• Social Network Analysis (SNA)– Why is it relevant?

– What is it?

– How does it work?

• Example applications– Washington Regional Pawn Data Sharing System

– Florida Department of Corrections


Why is SNA Relevant?

• Adversaries across the spectrum of conflict and crime are using network centric operations– Cheap and easy to move information

– Movement of information is hard to detect

– Conflict is now a game of hide and seek

• Analysts must find adversaries and their activities– Collect far more data than analysts can process

– Vast majority of the data is irrelevant

– Key to finding relevant data is relationships between entities

– Automated filtering and analysis is needed

• SNA can be used to filter and analyze data in the context of relationships between entities


What is SNA?

• The mapping, measuring and analysis of relationships and flows between people, groups, organizations, computers or other entities

• Nodes in the network represent entities while the edges show relationships or flows between the nodes

• Not a fixed methodology, but a collection of strategies for analyzing network data

• Applicable to a wide variety of domains involving complex systems

SNA


How does SNA work?

Source: Stocker, R., Green, D. G., and Newth, D. (2001) Consensus and Cohesion in Simulated Social Networks, Journal of Artificial Societies and Social Simulation, Vol 4, No 4.http://jasss.soc.surrey.ac.uk/4/4/5.html

Fully Connected Regular

Random

• Typically not interested in – Fully connected networks

– Regular networks

– Random networks


How does SNA work?

Source: Stocker, R., Green, D. G., and Newth, D. (2001) Consensus and Cohesion in Simulated Social Networks, Journal of Artificial Societies and Social Simulation, Vol 4, No 4. http://jasss.soc.surrey.ac.uk/4/4/5.html

Number of Links

Nu

mb

er o

f N

od

es

• Scale free networks– Connections are not randomly

distributed

– Connections are not randomly added

– Distribution of node connections follows the Power Law

– Small world theory

• Scale free networks occur in many domains involving complex systems


How does SNA work?

• Roles– Leaders

– Gatekeepers

– Outliers

• Structure– Subgroups

– Bridges

– Holes

• Processes– Flow

– Evolution

– Resilience

Scattered Clusters Hub

Multi-Hub Core/periphery

Source: Krebs, V. And Holley, J. Building Sustainable Communities Through Network Building. http://www.orgnet.com/BuildingNetworks.pdf


How does SNA work?

Boy Tarzan

TambaBuli

Cheetah

Jane

Bonzo

JungleJim George Ursula

Kite Network developed by David Krackhardt

• Degree

• Betweeness

• Closeness

Node Metrics


How does SNA work?

Boy Tarzan

TambaBuli

Cheetah

Jane

Bonzo

JungleJim George Ursula

Kite Network developed by David Krackhardt

• Degree distribution

• Betweeness distribution

• Average path length

Network Metrics

• Clustering coefficient

• Degree

• Betweeness

• Closeness

Node Metrics


Aerospace Data Mining Toolkit

Data

Data

Data

Data

Warehouse

Link Discovery

Analysis

PatternAnalysis

PredictiveAnalysis

Social NetworkAnalysis

Cleansing & Conditioning

Results

Pattern-basedquery

Entity-basedquery

All links query

Iterativequery

Input


Temporal Network


Summary

• Analysts are overwhelmed with massive amounts of data and automated filtering and analysis is needed.

• SNA can be used to filter and analyze data in the context of relationships between entities.

• Aerospace projects are applying data mining and SNA in novel ways to address the needs of our public safety partners.

• Because of the versatility of SNA, applications to new problems and domains are expected in the future.

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