This document provides an introduction to social network analysis and complex systems. It defines social networks as relationships between social entities like people and organizations. Nodes represent entities and edges represent relationships. Examples of social networks include migratory bird networks and a U.S. high school friendship network. Social network analysis is useful because human behavior is influenced by others in social contexts. Key concepts discussed include centrality measures, the small world phenomenon, and how social networks are examples of complex systems.

1. Introduction to Complex Systems
and Social Network Analysis
Arif Khan
Complex Systems Research Centre
The University of Sydney
Lecturer (on leave)
Department of CSE, BRAC University
This work is licensed under a Creative Commons AttributionNonCommercial-ShareAlike 4.0 International License.

2. What is Social Networks
• Relationship between Social Entities
B
A
D
C
Nodes are Entities/Actors
Can be people, organization,
countries
Edges are relationship
Can be Friendship, Transaction,
Trust, Relationship

3. Some Social Network
• Migratory Bird Network

4. Some Social Networks
• Relationship network in a U.S. high school. Girls are pink, boys
are blue

5. Some Social Network
• Ingredients Network

6. Why Social Network Analysis?
• Because our choice/behavior has social
context, we are influenced by others

7. Some Research Facts
• Relationships are mostly mutual. If you like
me, I will like you.
A
B
• Friend of my friend will eventually be my
Friend
C
A
B

8. Some Research Facts
• Making and Maintaining friendship is costly.
• Average person can maintain only 150
intimate relationship.
• So this friendship network is hardly possible.

9. Some Research Facts
• This is a small world. On average each person
of world has a friendship distance of 6
• There are on average 3.74 people in between
any two facebook users.

10. Complex System
• Social Networks are one type of Complex
System, they have all the properties discussed
above.
• Complex Systems
– Have large number of actors/nodes
– Changes over time
– They are resilient.

11. Centrality: finding important Nodes
• Degree Centrality
I am So
popular!!
C
A
B
B
B has high in-Degree
D
C
A
E
E
D
B has high out-Degree

12. Centrality: finding important Nodes
• Betweenness Centrality
‘A’ has high Betweenness centrality
It can control Information, can control business,
Can manipulate information

13. Centrality: finding important Nodes
• Closeness centrality
I may not have
lots of friend. But
I have powerful
friend, enough
for me
High (not highest)
closeness centrality

14. Example of SNA software (Gephi)
• Analyze my Facebook network
• <OPEN GEPHI outside>

15. Social Network Analysis as CSE
perspective
• Developing efficient algorithms (graph
algorithm, approximation algorithm)
• Developing efficient graph/mathematical
models of real world Social Networks
• Developing data mining software, centrality
measures
• And many more…

16. If you are interested…
• This is relative new research area.
• Almost all universities have research centers
related to Social Network analysis, complex
system, data mining etc.
• Complete the online course (FREE!) from
www.coursera.org/course/sna

17. THANK YOU
Questions?
Important Links: www.coursera.org/course/sna
My Mail: arif.khan@sydney.edu.au
Pictures taken from various sources, may be copyrighted. Used for Educational purpose only