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Introduction to complex systems and social network analysis


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This Presentation was prepared by Arif Khan
for the Seminar on Introduction to complex systems and social network analysis on 05/03/14 (Wednesday) Organized by BRAC University CSE Department in collaboration with BRAC University Computer Club (BUCC).

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Introduction to complex systems and social network analysis

  1. 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. 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. 3. Some Social Network • Migratory Bird Network
  4. 4. Some Social Networks • Relationship network in a U.S. high school. Girls are pink, boys are blue
  5. 5. Some Social Network • Ingredients Network
  6. 6. Why Social Network Analysis? • Because our choice/behavior has social context, we are influenced by others
  7. 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. 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. 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. 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. 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. 12. Centrality: finding important Nodes • Betweenness Centrality ‘A’ has high Betweenness centrality It can control Information, can control business, Can manipulate information
  13. 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. 14. Example of SNA software (Gephi) • Analyze my Facebook network • <OPEN GEPHI outside>
  15. 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. 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
  17. 17. THANK YOU Questions? Important Links: My Mail: Pictures taken from various sources, may be copyrighted. Used for Educational purpose only