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The Basics of Social Network Analysis

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Rory Sie
Rory Sie

An introduction in the world of Social Network Analysis and a view on how this may help learning networks. History, data collection and several analysis techniques are shown.

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The Basics of Social Network Analysis ,[object Object],[object Object]
Outline ,[object Object],[object Object],[object Object],[object Object]
History Social Network Analysis Psychology Anthropology
1930s: Jacob Moreno http://institutomomento.wordpress.com sociogram
1950s: Cartwright and Harary Dorwin Cartwright http://www.rcgd.isr.umich.edu http://www.ur.umich.edu Frank Harary + - - A B C “ any balanced graph can be divided into two cohesive sub-groups that are in conflict with each other”
1920s: Warner and Mayo Mayo Warner Hawthorne http://administracion1enlinea.blogspot.com http://www.wolframalpha.com effect focus on relationships
1920s: Warner and Mayo Mayo Warner http://administracion1enlinea.blogspot.com http://www.wolframalpha.com adapted from Scott, 2000 cliques every person is separated by only one step
Social Networks ,[object Object],[object Object],A B C D E A-B-C-E
Mark Granovetter ,[object Object],[object Object],://www.stanford.edu/dept/soc/people/mgranovetter/
History Social Network Analysis Psychology Anthropology Hawthorne Networks Graph theory Sociogram Graph theory Strength of weak ties
Examples centrality = power (Krackhardt, 1990) ‘ broker’ (Burt, 2004)
Why? ,[object Object],[object Object],[object Object],[object Object],adapted from Liebowitz, 2005
Data collection
Ego network ego network but.... self-perceived ask for connections ask connections if they are connected alter alter
Snowball method but.... self-perceived ask for connections ask connections for their connections until you reach a stopping criterion
Complete networks monitor email traffic or monitor tweets
Data storage Adjacency matrix (R, UCINET)
Data storage ,[object Object],[object Object],[object Object],[object Object],GML/ XGMML (Cytoscape, Gephi)
Data storage Pajek network (Pajek, UCINET)
Analysis: network ,[object Object],[object Object],[object Object],A D C B E
Analysis: community ,[object Object],A D C B E F every person in a clique can be reached within 1 step
Analysis: community ,[object Object],A D C B E F every person can be reached within n steps. ABCF is a 2-clique
Analysis: community A D C B E F Faction http://www.physorg.com/news/2011-01-mathematical-groups-factions.html
Analysis: individual A D C B E F G H Betweenness network is dependent on C Degree G is very popular 12 12 14 17 17 18 19 19 Closeness C and G can easily reach others
Summary ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
References ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Questions? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
NOW: PLN Drawing ,[object Object],[object Object],[object Object],[object Object]

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The Basics of Social Network Analysis

  • 1.
  • 2.
  • 3. History Social Network Analysis Psychology Anthropology
  • 4. 1930s: Jacob Moreno http://institutomomento.wordpress.com sociogram
  • 5. 1950s: Cartwright and Harary Dorwin Cartwright http://www.rcgd.isr.umich.edu http://www.ur.umich.edu Frank Harary + - - A B C “ any balanced graph can be divided into two cohesive sub-groups that are in conflict with each other”
  • 6. 1920s: Warner and Mayo Mayo Warner Hawthorne http://administracion1enlinea.blogspot.com http://www.wolframalpha.com effect focus on relationships
  • 7. 1920s: Warner and Mayo Mayo Warner http://administracion1enlinea.blogspot.com http://www.wolframalpha.com adapted from Scott, 2000 cliques every person is separated by only one step
  • 8.
  • 9.
  • 10. History Social Network Analysis Psychology Anthropology Hawthorne Networks Graph theory Sociogram Graph theory Strength of weak ties
  • 11. Examples centrality = power (Krackhardt, 1990) ‘ broker’ (Burt, 2004)
  • 12.
  • 14. Ego network ego network but.... self-perceived ask for connections ask connections if they are connected alter alter
  • 15. Snowball method but.... self-perceived ask for connections ask connections for their connections until you reach a stopping criterion
  • 16. Complete networks monitor email traffic or monitor tweets
  • 17. Data storage Adjacency matrix (R, UCINET)
  • 18.
  • 19. Data storage Pajek network (Pajek, UCINET)
  • 20.
  • 21.
  • 22.
  • 23. Analysis: community A D C B E F Faction http://www.physorg.com/news/2011-01-mathematical-groups-factions.html
  • 24. Analysis: individual A D C B E F G H Betweenness network is dependent on C Degree G is very popular 12 12 14 17 17 18 19 19 Closeness C and G can easily reach others
  • 25.
  • 26.
  • 27.
  • 28.

Editor's Notes

  1. Thank you for your attention, and I hope to see you at the Career day