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Manila, Philippines 28-30 April 2008

Session 2 - Social Network Analysis Concepts and terminology Examples of application in Public Health. Steeve Ebener, WHO. Manila, Philippines 28-30 April 2008. 2. Content. 1. What is a network ? Network types Mode Ego / Complete network Ego network Measures Complete network

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Manila, Philippines 28-30 April 2008

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  1. Session 2 -Social Network AnalysisConcepts and terminologyExamples of application in Public Health Steeve Ebener, WHO Manila, Philippines 28-30 April 2008

  2. 2 Content 1 • What is a network ? • Network types • Mode • Ego / Complete network • Ego network • Measures • Complete network • structure • Measures (centrality, centralization, cohesion) • Efficient network form ? • Examples of application in Public health 3

  3. What is a Network ? • A set of actors (node, points) • individuals (e.g. persons) • collectivities (e.g. firms, nations,...) • A set of ties (links, lines, edges, arcs) of a given type that connect pairs of actors Set of ties of a given type constitutes a social relation Borgatti

  4. What is a Network ? Taxonomy of network ties among persons Borgatti

  5. What is a Network ? Directed vs undirected ties • Undirected relations (ties) • attended meeting with • Communicate daily with • Directed relations (ties) • Lent money to Borgatti

  6. What is a Network ? Strength of tie • We can attach values to ties, representing quantitative attributes • Strength of relationship • Information capacity of tie • Rate of flow or traffic across tie • Distance between node • Probabilities of passing on information • Frequency of interaction Borgatti

  7. Network types Borgatti

  8. Network types • 1 mode network • Network composed of two types of social entities (say persons and organizations) • Network composed of only one types of social entities (e.g. persons or organization). • 2 mode network • offers interesting analytical possibilities for gaining a greater understanding of "macro-micro" relations

  9. Network types Beware the Micro/Macro distinction • But in network research... • In organization studies • Micro means focus on actors • which could be firms... • Micro refers to studies in which the actors are persons • personality -> Status • Macro means focus on the network in which actors are embedded • Macro refers to studies in which the actors are firms • Firm size -> Profits Borgatti

  10. Network types • Ego network • All the actors of a network with all the ties which exists among them. • A focal actor (the • respondent, called • ego), together with the actor's contacts (called alters), and often, a limited set of ties among the alters. • Complete network Borgatti

  11. Network types Borgatti

  12. Ego Network Measures Just picked one: • PN Exposure Hanneman

  13. Ego Network Personal Network (PN) Exposure • Degree to which an individual is exposed to an innovation through his/her personal network. • Network exposure provides: • 1. awareness information • 2. influence/persuasion • 3. detailed information on how to get the innovation, possible problems, updates, refills, enhancements, novel uses • 4. something to talk about • 5. ... Valente

  14. Ego Network Personal Network (PN) Exposure = Non User = User PN Exposure=33% PN Exposure=66% PN Exposure=100% 14 Valente

  15. Complete Network Structure (shape) Large variety two examples: • Core/Periphery structure • Network consists of single group (a core) together with hangers-on (a periphery) • Core connects to all • Periphery connects only to the core • Short distances, good for transmitting information • Identification with group as whole • Clique structure • Multiple subgroups of factions • Identity with subgroup • Diversity of norms, belief Borgatti

  16. Complete Network Two main measures • Centrality & Centralization • Degree centrality • Eigenvector centrality • Closeness centrality • Betweeness centrality • Centralization • ... • Cohesion • Density • Distance • Transitivity • ...

  17. Complete Network Centrality & Centralization • Networks Analysis can be used to identify positions/role in the network • One significant position is finding the person or people at the center • Centrality has been a central preoccupation with network analysis • There are many ways to identify central persons (centrality) and rate who near the center each node is. Valente

  18. Complete Network Centrality & Centralization • Local centrality vs. global centrality • Local centrality - when a point has a large number of connections to other points in its immediate environment. • Global centrality - has a strategic position within the network. • Centralization • overall centrality of the network Valente

  19. Complete Network Centrality Borgatti

  20. Complete Network Centrality • Degree: the most active or popular node in the network • Closeness: the most independent node and the one in excellent position to monitor the information flow in the network. • betweenness: The most powerful broker or gatekeeper in the network • Eigenvector: the most popular ("in the know") node in the network

  21. Complete Network Centralization Decentralized Centralized Valente

  22. Complete Network Peripheral players • Most people would view the nodes on the periphery of a network as not being very important. In fact, since individuals' networks overlap, peripheral nodes are connected to networks that are not currently mapped. • These nodes might have their own network outside of the company - making them very important resources for fresh information not available inside the company! Valente

  23. Complete Network Ties as conduits • Certain ties can serve as pipes or roads that enable flows/traffic (and in their absence, prevent it) • information, solutions, material aide, resources • Attitudes, behaviors, practices • Interpersonal models of diffusion, influence Borgatti

  24. Complete Network Flow processes • Path: can't repeat node • 1-2-3-4-5-6-7-8 • virus: host become immune or die • Trail: can't repeat line • 1-2-3-1-7-8 • gossip • Walk: unrestricted • 1-2-3-1-2-7-1-7-1 • Dollar bill moving through economy Borgatti

  25. Complete Network Cutpoints and Bridges • Bridge: a tie that, if removed, would increase the number of components • Cutpoint: a node which, if removed, would increase the number of components • If a tie is a bridge, at least one if its endpoints must be a cutpoint Borgatti

  26. Complete Network Cutpoints and Bridges • Bridge: a tie that, if removed, would increase the number of components Borgatti

  27. Complete Network Other node related concepts • Dyad - two individuals (as husband and wife, mother and son) maintaining a sociologically significant relationship • adjacent - two points connected by a line • neighborhood - set of adjacent points Valente

  28. Complete Network Cohesion Length & Distance • Length of a path/trail/walk is the number of links it has • Distance between two nodes is the length of the shortest path They rules: http://www.theyrule.net/ • The shortest the average distance the faster the information flows Borgatti

  29. Complete Network Cohesion Density • Proportion of pairs of actors that are actually tied • b) is more dense than a) The higher the density of the group, the more at risk (disease spread) Borgatti

  30. Complete Network Cohesion Transitivity • Number of transitive triples divided by the number of potential ones (number of paths of length 2) • The higher the percent of transitive triads the more cohesive the network Borgatti

  31. Efficient network form ? • Finding efficient forms may completely depend on behavior being studied • a dense network facilitate information flow but also diseases transmission • What is the trade off between individual satisfaction and network-level performance? • Can optimal forms be created or are the most optimal ones those that exist? Valente

  32. Examples of application in PH Analysis of the DTTB program Objective "To enhance the social and professional support system of the DTTB participants, with the end view of improving diagnostic capability and facilitate their integration into a new health network" Several phases study: • Develop a better understanding of the knowledge flows and gaps of DTTBs • Analyze the connection and speed of transfer of information within the health system. • Determine the impact of geography and connectivity (ICT) on the DTTBs care delivery capacities.

  33. Logbook Examples of application in PH Analysis of the DTTB program Process SNA software Analysis

  34. Examples of application in PH Relations among drug injectors Which two people should be isolated in order to slow spread of HIV ? Bridges between groups represent key pathways for disease spread. Borgatti

  35. Examples of application in PH Colorado Springs Sexual Contact Network SOURCE: James Moody. http://www.soc.sbs.ohio-state.edu/

  36. Examples of application in PH Health promotion • Network data may help improve health promotion programs • The Messenger is the Message • Identify opinion leaders (over 15 studies) • Identify leaders and match them to nominees • Identify groups and find leaders within Snowball/Respondent driven sampling for recruitment (VPS) Valente

  37. Examples of application in PH Community of practice building • Mapping the extend of a new community of practice and identify knowledge hubs through snow ball survey. • Potential • leaders for this • community • Measuring the success of communities • of practice

  38. Examples of application in PH Knowledge continuity analysis http://www.orgnet.com/experts.html

  39. Examples of application in PH Assessing the current state of collaboration

  40. Examples of application in PH Visualisation

  41. Information and persuasion flow through social networks. Inter-organizational collaboration, coordination, and cooperation. Analysis of the surveillance network efficiency ... Examples of application in PH and some more... Valente

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