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Social Network Analysis - Visualization

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Lee Taemin

Ajith Abraham, Computational social network analysis : trends, tools and research advances (Dordrecht: Springer, 2010). CH1. An Overview of Methods for Virtual Social Networks Analysis

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An Overview of Methods for Virtual Social Networks Analysis Part 2 TMLee (persuade@gmail.com)
Index 1.4.2. Network Data Visualization Graphs Matricies Maps Hybrid Appraoch 1.5. Application Scenario : The Case of LinkedIn First Phase Second Phase 1.6. Conclusion
1.4.2. Network Data Visualisation Definition Any technique used to create images, diagrams, or animations in order to communicate a message Why we needs this? Quickly communicate rich messages ( communication ) Discover new, previously unknown facts and relationships ( discovery ) Get better insight into things we already know ( insight )
Communication, Discovery, Insight
1.4.2.1. Graphs A graph is a structure used for modelling information Components Nodes ( actors ) Edges ( communication paths ) F D E A B C
1.4.2.1. Graphs Types of Graphs Undirected Graph Directed Graph Weighted Graph Planar Graph Orthogonal Graph Grid-based Graph
1.4.2.1. Graphs Morenos social graph
1.4.2.1. Graphs An example of graph for network analysis
1.4.2.1. Graphs Layout algorithms
1.4.2.2. Matrices A matrix is a rectangular array of elements, which can be numbers. F D E A B C
1.4.2.2. Matrices Types of matrices. Row matrix Column matrix Square matrix Identity matrix Digonal matrix Skew-symmetric matrix Symmetric matrix Triangular matrix
1.4.2.2. Matrices Raw data, Matrix, Graph Q: I want to find sociological information. Who is the outsider ? Robert likes Sara. Sara likes Ray. Ray likes Justine. Justine likes nobody but Ray. Sara also likes Robert. Ray likes Sara. Robert likes Ray. Ray likes Robert
1.4.2.3. Maps
1.4.2.3. Maps
1.4.2.4. Hybrid Approach
1.5. Application Scenario : The Case of LinkedIn Analyse the Virtual Social Networks LinkedIn.
1.5.1. First Phase Gathering social information by ego-centric approach. Ego-centric approach Questionnaire Answer Q1 : How many actors have you been in ragular contact with in the last 7 days? Q2 : Please name the actors and indicate the gender and the age. Q3 : Of the actors you have regular contact how many are - Sex-partners - Friends - Acquaintances Q4 : Please indicate which of the actors you have named have been in regular contact with any of the other actors you have named Q1 : 11 Q2 : Ray(M,22), Crystal(M,23), Livia(F,30), Justine(F, 26), SaraM(F, 28), Victor(M,32), Hallio(M,36), Blaine(M,29), Kellan(M,28), Jacx(M,30), Sara(F,27) Q3 : - Sex-partners : 1 (Sara) - Friends : 8 - Acquaintances : 2 (Blaine; Jacx) Q4 : Crystal is in regular contact with Victor Livia has been in regular contact with Sara, Victor, and Justine Justine: is in regular contact with Livia, Sara, and SaraM SaraM: is in regular contact with Sara, Justine, Kellan, Bleine, and Hallio Victor is in regular contact with Crystal, Hallio, and Livia Hallio is in regular contact with Victor, SaraM, Bleine, and Jacx Bleine is in regular contact with Hallio, Jacx, Sara, and SaraM Kellan is in regular contact with SaraM Jacx has in regular contact with Blaine, Hallio, and Sara Sara is in regular contact with Livia, Blaine, and SaraM Robert
1.5.1. First Phase Ego-centric approach
1.5.2. Second Phase Focused on the dynamics of the overall social group Socio-centric approach Questionnaire Q1 : How close is to you? Q2 : How comfortable do you feel to discuss with ? Q3 : How much do you trust ? Answer
1.6. Conclusion In Chapter 1, Definition of Virtual Social Networks The motivations that lead people to join Virtual Social Networks. Virtual Social Network analysis Data collection Visualization Communication Discovery Insight

More Related Content

Social Network Analysis - Visualization

  • 1. An Overview of Methods for Virtual Social Networks Analysis Part 2 TMLee (persuade@gmail.com)
  • 2. Index 1.4.2. Network Data Visualization Graphs Matricies Maps Hybrid Appraoch 1.5. Application Scenario : The Case of LinkedIn First Phase Second Phase 1.6. Conclusion
  • 3. 1.4.2. Network Data Visualisation Definition Any technique used to create images, diagrams, or animations in order to communicate a message Why we needs this? Quickly communicate rich messages ( communication ) Discover new, previously unknown facts and relationships ( discovery ) Get better insight into things we already know ( insight )
  • 5. 1.4.2.1. Graphs A graph is a structure used for modelling information Components Nodes ( actors ) Edges ( communication paths ) F D E A B C
  • 6. 1.4.2.1. Graphs Types of Graphs Undirected Graph Directed Graph Weighted Graph Planar Graph Orthogonal Graph Grid-based Graph
  • 7. 1.4.2.1. Graphs Morenos social graph
  • 8. 1.4.2.1. Graphs An example of graph for network analysis
  • 10. 1.4.2.2. Matrices A matrix is a rectangular array of elements, which can be numbers. F D E A B C
  • 11. 1.4.2.2. Matrices Types of matrices. Row matrix Column matrix Square matrix Identity matrix Digonal matrix Skew-symmetric matrix Symmetric matrix Triangular matrix
  • 12. 1.4.2.2. Matrices Raw data, Matrix, Graph Q: I want to find sociological information. Who is the outsider ? Robert likes Sara. Sara likes Ray. Ray likes Justine. Justine likes nobody but Ray. Sara also likes Robert. Ray likes Sara. Robert likes Ray. Ray likes Robert
  • 16. 1.5. Application Scenario : The Case of LinkedIn Analyse the Virtual Social Networks LinkedIn.
  • 17. 1.5.1. First Phase Gathering social information by ego-centric approach. Ego-centric approach Questionnaire Answer Q1 : How many actors have you been in ragular contact with in the last 7 days? Q2 : Please name the actors and indicate the gender and the age. Q3 : Of the actors you have regular contact how many are - Sex-partners - Friends - Acquaintances Q4 : Please indicate which of the actors you have named have been in regular contact with any of the other actors you have named Q1 : 11 Q2 : Ray(M,22), Crystal(M,23), Livia(F,30), Justine(F, 26), SaraM(F, 28), Victor(M,32), Hallio(M,36), Blaine(M,29), Kellan(M,28), Jacx(M,30), Sara(F,27) Q3 : - Sex-partners : 1 (Sara) - Friends : 8 - Acquaintances : 2 (Blaine; Jacx) Q4 : Crystal is in regular contact with Victor Livia has been in regular contact with Sara, Victor, and Justine Justine: is in regular contact with Livia, Sara, and SaraM SaraM: is in regular contact with Sara, Justine, Kellan, Bleine, and Hallio Victor is in regular contact with Crystal, Hallio, and Livia Hallio is in regular contact with Victor, SaraM, Bleine, and Jacx Bleine is in regular contact with Hallio, Jacx, Sara, and SaraM Kellan is in regular contact with SaraM Jacx has in regular contact with Blaine, Hallio, and Sara Sara is in regular contact with Livia, Blaine, and SaraM Robert
  • 18. 1.5.1. First Phase Ego-centric approach
  • 19. 1.5.2. Second Phase Focused on the dynamics of the overall social group Socio-centric approach Questionnaire Q1 : How close is to you? Q2 : How comfortable do you feel to discuss with ? Q3 : How much do you trust ? Answer
  • 20. 1.6. Conclusion In Chapter 1, Definition of Virtual Social Networks The motivations that lead people to join Virtual Social Networks. Virtual Social Network analysis Data collection Visualization Communication Discovery Insight

Editor's Notes

  1. 讌豌 語 , CD 讌 , Communication : 企一 Discovery : Small World problem Insight : Social Network .. 螳 豺 覈詩 -_-; 朱 4 螳讌 visualization technique 襯 る蟆 . 1) graph, 2) matrix, 3) map, 4) hybrid
  2. CH11. pic 11.2 ~ 11.4 All student -> 17 student -> 10 student.
  3. each node can represents an actor, single or group, or a topic and each link (arc) represents the connection between couples of actors or topics. M. C. Caschera, F. Ferri, and P. Grifoni, [27] SIM: A dynamic multidimensional visualization method for social networks, PsychNology Journal 6, no. 3 (2008): 291-320.
  4. Planar graph : edge 伎 intersection 覦讌 蟆 蠏碁Υ graph. 覦讌 蟆 蠏碁Π graph plane graph or planar embedding of the graph 手 . J Bondy, Graph theory with applications (New York: American Elsevier Pub. Co., 1976). 135 p http://en.wikipedia.org/wiki/Planar_graph Planar Graph : 覃 蠏碁 planar graph 覈 螳讌 譬 轟煙 螳讌螻 . 螳 譴 煙 覈 planar graph sparse る 蟆企 . Euler 螻旧 (Eulers formula) Edge E Vertex V 襦 企伎 Graph | E| <= 3|V| -6 覦 . 讀 , Edge 螳螳 linear 覲伎譯朱 蟆企 . 覈 planar graph vertex degree 螳 襷 5 企 . 蠏碁蠍 覓語 るジ graph polynomial time 願屋讌 螻襴讀 planar graph 伎 襷れ 觜襯願 . 蠏碁Μ螻 planar graph subgraph planar 企 . http://mybox.happycampus.com/yangpa09/645528
  5. [22] Who Shall Survive? Nervous and Mental Disease Publishing
  6. Relationship between actors Subgroups Characteristics of the Virtual Social Networks Spring-embedding (force-directed) algorithm 碁螳 譟伎 , 覲願鍵 譬 襦 郁 蠏碁 . Bernes-Hut algorithm [ 朱 ] used to efficiently compute n -body (repulsion) forces and numerical integration routines are used to smoothly update screen positions. [Vizster 朱 ] community structures Newman's community identification algorithm [ 朱 ] it provides useful topology-based groupings fast enough to support real-time interaction. [Vizster 朱 ]
  7. Left : Kamada-Kawai Algorithm Right : Vmap-layout Algorithm
  8. The matrix-based approach associates the network actors with rows and columns; the matrix cell values identify social connections between actors. M. C. Caschera, F. Ferri, and P. Grifoni, [27] SIM: A dynamic multidimensional visualization method for social networks, PsychNology Journal 6, no. 3 (2008): 291-320.
  9. Row matrix or Row vector Column matrix or Column vector Square matrix : 覦 Identity matrix : Digonal matrix : 螳 Symmetric matrix : 豺 Skew-symmetric matrix : 覦豺 Triangular matrix : 3 螳 ( 蠏碁殊 3 螳 )
  10. newsmap, http://newsmap.jp/ . The map-based visualization is suitable to show and organize large volumes of data and complex social networks data structures emphasizing textural or conceptual features of the visualization by shading, colours, labelling and icons. M. C. Caschera, F. Ferri, and P. Grifoni, [27] SIM: A dynamic multidimensional visualization method for social networks, PsychNology Journal 6, no. 3 (2008): 291-320.
  11. B. A. Nardi et al., [25] Contact Map : integrating communication and information through visualizing personal social networks, Communications of the ACM 45, no. 4 (2002): 89.
  12. M. C. Caschera, F. Ferri, and P. Grifoni, [27] SIM: A dynamic multidimensional visualization method for social networks, PsychNology Journal 6, no. 3 (2008): 291-320.
  13. http://blog.hubspot.com/blog/tabid/6307/bid/4514/Making-Friends-LinkedIn-vs-Facebook-vs-Twitter-cartoon.aspx
  14. http://manyeyes.alphaworks.ibm.com/manyeyes/