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Facebook Networks
Analysis
Mojtaba Khodadadi
Advisor: Dr. Farhad Shahbazi
May 2014
• Gephi: is an interactive visualization and
exploration platform for all kinds of
networks and complex systems, dynamic
and hierarchical graphs.
Introduction
Introduction
• Netvizz: is a tool that extracts data from
different sections of the Facebook platform
(personal profile, groups, pages) for
research purposes. File outputs can be
easily analyzed in standard software.
Introduction
Introduction
• Density: Measures how close the network
is to complete. for complete graph
density=1.
• Average Clustering Coefficient: The
mean value of individual coefficients.
• Diameter: The longest graph distance
between any two nodes in the network.
• Betweenness Centrality: Measures how
often a node appears on shortest paths
between nodes in the network.
Definitions
Definitions
• Closeness Centrality: The average
distance from a given starting node to all
other nodes in the network.
• Eccentricity: The distance from a given
starting node to the farthest node from it
in the network.
• Clustering Coefficient: Indicates how
nodes are embedded in their
neighborhood. (“What is the probability
that two of my friends are also friends?”)
• Type: page like network
• Likes: 631,000
page like network: This module starts with a
selected page (the "seed") and retrieves all
the pages that page likes. It will continue
until the specified crawl depth is reached
(currently limited to 2). The output is a
network containing a (directed) network of
pages.
First Network: “ ”
First Network: “ ”
• Nodes: 34
• Edges: 72
• Directed
• Unweighted
• Avg degree: 2.118
• Graph density: 0.064
• Diameter: 4
• Avg path length: 2.632
• # shortest paths: 443
• Modularity: 0.66
• # communities: 5
• Avg clustering coef: 0.663
• Total Triangles: 30
First Network: “ ”
• Degree distribution
First Network: “ ”
• Betweenness Centrality distribution
First Network: “ ”
• Closeness Centrality distribution
First Network: “ ”
• Eccentricity distribution
First Network: “ ”
First Network: “ ”
• Nodes are ranked by betweenness centrality
• Clustering coefficient distribution
First Network: “ ”
• Nodes are ranked by clustering coefficient
First Network: “ ”
• Communities size distribution
First Network: “ ”
First Network: “ ”
• Nodes are ranked by betweenness centrality
• Type: like network
like network: This module creates a network
from your friends and their likes (both users
and liked objects are nodes). Only liked
pages are taken into account, not external
objects.
Second Network: “my facebook like network”
Second Network: “my facebook like network”
• Nodes: 8559
• Edges: 14015
• Directed
• Unweighted
• Avg degree: 1.637
• Graph density: 0.000
• Diameter: 1
• Avg path length: 1.0
• # shortest paths: 14015
• Modularity: 0.578
• # communities: 38
• Avg clustering coef: 0
• Total Triangles: 0
Second Network: “my facebook like network”
• Type: personal friend network
personal friend network: This module
creates a network with all the friendship
connections in your personal network
Third Network: “my facebook friends network”
Third Network: “my facebook friends network”
• Nodes: 68
• Edges: 620
• Directed
• Unweighted
• Avg degree: 7.647
• Graph density: 0.114
• Diameter: 5
• Avg path length: 1.825
• # shortest paths: 1524
• Modularity: 0.209
• # communities: 7
• Avg clustering coef: 0.548
• Total Triangles: 1833
Third Network: “my facebook friends network”
• Type: group
• Members: 3597
Group network: This module creates a
network with all the friendship connections
in the group.
Forth Network: “IUT” group
Forth Network: “IUT” group
• Nodes: 3597
• Edges: 30691
• Directed
• Unweighted
• Avg degree: 8.532
• Graph density: 0.002
• Diameter: 14
• Avg path length: 3.766
• # shortest paths: 2701550
• Modularity: 0.564
• # communities: 304
• Avg clustering coef: 0.285
• Total Triangles: 74277
Forth Network: “IUT” group
• Degree distribution => scale-free network
Forth Network: “IUT” group
• Type: group
• Members: 2813
Group network: This module creates a
network with all the friendship connections
in the group.
Fifth Network: “ ” group
Fifth Network: “ ” group
• Nodes: 2813
• Edges: 10251
• Directed
• Unweighted
• Avg degree: 7.288
• Graph density: 0.003
• Diameter: 13
• Avg path length: 4.526
• # shortest paths: 4543398
• Modularity: 0.653
• # communities: 666
• Avg clustering coef: 0.287
• Total Triangles: 17515
Fifth Network: “ ” group
• Degree distribution => scale-free network
Fifth Network: “ ” group
• “Quantum Information and Quantum Computer
Scientists of the World Unite” group (1945
members): scale-free behaviour
• “Bill Gates” page (10,171,680 likes): scale-free
behaviour
• “I fucking love science” page (15,887,023
likes): scale-free behaviour
Other Network that I analyzed
References
• “Studying Facebook via data extraction: the Netvizz application”, B.
Rieder, Proceedings of the 5th Annual ACM Web Science Conference,
Pages 346-355, DOI: 10.1145/2464464.2464475
• Netvizz: https://apps.facebook.com/netvizz/
• “Gephi: an open source software for exploring and manipulating
networks”, M Bastian, S Heymann, M Jacomy - ICWSM, 2009.
• Gephi: https://gephi.org/

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Facebook Networks Analysis

  • 2. • Gephi: is an interactive visualization and exploration platform for all kinds of networks and complex systems, dynamic and hierarchical graphs. Introduction
  • 4. • Netvizz: is a tool that extracts data from different sections of the Facebook platform (personal profile, groups, pages) for research purposes. File outputs can be easily analyzed in standard software. Introduction
  • 6. • Density: Measures how close the network is to complete. for complete graph density=1. • Average Clustering Coefficient: The mean value of individual coefficients. • Diameter: The longest graph distance between any two nodes in the network. • Betweenness Centrality: Measures how often a node appears on shortest paths between nodes in the network. Definitions
  • 7. Definitions • Closeness Centrality: The average distance from a given starting node to all other nodes in the network. • Eccentricity: The distance from a given starting node to the farthest node from it in the network. • Clustering Coefficient: Indicates how nodes are embedded in their neighborhood. (“What is the probability that two of my friends are also friends?”)
  • 8. • Type: page like network • Likes: 631,000 page like network: This module starts with a selected page (the "seed") and retrieves all the pages that page likes. It will continue until the specified crawl depth is reached (currently limited to 2). The output is a network containing a (directed) network of pages. First Network: “ ”
  • 10. • Nodes: 34 • Edges: 72 • Directed • Unweighted • Avg degree: 2.118 • Graph density: 0.064 • Diameter: 4 • Avg path length: 2.632 • # shortest paths: 443 • Modularity: 0.66 • # communities: 5 • Avg clustering coef: 0.663 • Total Triangles: 30 First Network: “ ”
  • 11. • Degree distribution First Network: “ ”
  • 12. • Betweenness Centrality distribution First Network: “ ”
  • 13. • Closeness Centrality distribution First Network: “ ”
  • 15. First Network: “ ” • Nodes are ranked by betweenness centrality
  • 16. • Clustering coefficient distribution First Network: “ ”
  • 17. • Nodes are ranked by clustering coefficient First Network: “ ”
  • 18. • Communities size distribution First Network: “ ”
  • 19. First Network: “ ” • Nodes are ranked by betweenness centrality
  • 20. • Type: like network like network: This module creates a network from your friends and their likes (both users and liked objects are nodes). Only liked pages are taken into account, not external objects. Second Network: “my facebook like network”
  • 21. Second Network: “my facebook like network”
  • 22. • Nodes: 8559 • Edges: 14015 • Directed • Unweighted • Avg degree: 1.637 • Graph density: 0.000 • Diameter: 1 • Avg path length: 1.0 • # shortest paths: 14015 • Modularity: 0.578 • # communities: 38 • Avg clustering coef: 0 • Total Triangles: 0 Second Network: “my facebook like network”
  • 23. • Type: personal friend network personal friend network: This module creates a network with all the friendship connections in your personal network Third Network: “my facebook friends network”
  • 24. Third Network: “my facebook friends network”
  • 25. • Nodes: 68 • Edges: 620 • Directed • Unweighted • Avg degree: 7.647 • Graph density: 0.114 • Diameter: 5 • Avg path length: 1.825 • # shortest paths: 1524 • Modularity: 0.209 • # communities: 7 • Avg clustering coef: 0.548 • Total Triangles: 1833 Third Network: “my facebook friends network”
  • 26. • Type: group • Members: 3597 Group network: This module creates a network with all the friendship connections in the group. Forth Network: “IUT” group
  • 28. • Nodes: 3597 • Edges: 30691 • Directed • Unweighted • Avg degree: 8.532 • Graph density: 0.002 • Diameter: 14 • Avg path length: 3.766 • # shortest paths: 2701550 • Modularity: 0.564 • # communities: 304 • Avg clustering coef: 0.285 • Total Triangles: 74277 Forth Network: “IUT” group
  • 29. • Degree distribution => scale-free network Forth Network: “IUT” group
  • 30. • Type: group • Members: 2813 Group network: This module creates a network with all the friendship connections in the group. Fifth Network: “ ” group
  • 31. Fifth Network: “ ” group
  • 32. • Nodes: 2813 • Edges: 10251 • Directed • Unweighted • Avg degree: 7.288 • Graph density: 0.003 • Diameter: 13 • Avg path length: 4.526 • # shortest paths: 4543398 • Modularity: 0.653 • # communities: 666 • Avg clustering coef: 0.287 • Total Triangles: 17515 Fifth Network: “ ” group
  • 33. • Degree distribution => scale-free network Fifth Network: “ ” group
  • 34. • “Quantum Information and Quantum Computer Scientists of the World Unite” group (1945 members): scale-free behaviour • “Bill Gates” page (10,171,680 likes): scale-free behaviour • “I fucking love science” page (15,887,023 likes): scale-free behaviour Other Network that I analyzed
  • 35. References • “Studying Facebook via data extraction: the Netvizz application”, B. Rieder, Proceedings of the 5th Annual ACM Web Science Conference, Pages 346-355, DOI: 10.1145/2464464.2464475 • Netvizz: https://apps.facebook.com/netvizz/ • “Gephi: an open source software for exploring and manipulating networks”, M Bastian, S Heymann, M Jacomy - ICWSM, 2009. • Gephi: https://gephi.org/