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Social Network Analysis: Possibilities and Pitfalls

Social Network Analysis: Possibilities and Pitfalls. Dr Damon Alexander School of Social and Political Sciences University of Melbourne Email: dta@unimelb.edu.au The Power to Persuade Symposium Melbourne 5 September 2012.

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Social Network Analysis: Possibilities and Pitfalls

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  1. Social Network Analysis: Possibilities and Pitfalls Dr Damon AlexanderSchool of Social and Political SciencesUniversity of Melbourne Email: dta@unimelb.edu.au The Power to Persuade Symposium Melbourne 5 September 2012

  2. Social Network Analysis (SNA) has an incredibly diverse range of applications: • Track down Saddam Hussein • Map terrorist networks • Examine spread of disease • Map social capital • Map childhood friendship networks and how they change • Map rise to power of Medici clan in 14th century Florence • Map friendship networks between cows!

  3. Basic Concepts “A social network is a structure composed of a set of actors, some of whose members are connected by a set of one or more relations.” (Knoke and Yang, 2008) Key building blocks are: i)Actors(eg. individuals; organisations; nations) ii) Relations(can be any form of interaction between two or more actors eg. friendship network; kinship tie; advice network) -Uses ‘relational’ data rather than individual attributes (eg. age; IQ) -Structure/Agency Debate?

  4. Network Types • Complete Networks (‘whole’ or ‘global networks’) - Includes all actors in a given population (eg. All service providers in a service sector; all members of management team) -Can analyse properties such as structure; composition; density etc as well as properties of individuals in network -Data can be difficult to collect • Ego Networks (personal networks) -Consist of one actor (ego) and all other actors (alters) directly tied to ego. -Can analyse and compare properties of ego’s ties but can’t make assumptions about broader network. -Data easier to collect

  5. Example of ‘Complete Network’:Melville Strategic Information Network

  6. Example of ‘Ego Network’:Melville Mayor (Strategic Information)

  7. Data/Data Collection Can use SNA to analyse any data with ‘relational’ form. Examples: • Survey/interview data collected through name generators/name interpreters (who do you know…?) or contact matrices (how often do you see…?) • Documentary analysis (eg. Board directorships) • Historical data (eg. John Padgett’s rise of the Medici clan) • Analysis of group conversation based on video data. • Analysis of passes between players on soccer team • Analysis of links between political organisations based on hyperlinks from website to website.

  8. Measures/Tools for Analysis Centrality -In-Degree (measures ‘prominence’) -Out-Degree (measures ‘influence’) -Betweeness/Brokerage (measure extent of ‘connecting’ role) Density(measures extent to which actors are connected within network) External-Internal Index(measures ratio of in-group to out-group ties) Reach (measures actors ‘reach’ across network) *Can be used in conjunction with traditional quantitative measures

  9. Project Examples • Innovation Inside Government (Considine and Lewis) • Mapped advice/strategic information networks in 11 local govts • Social Connectivity Study (Considine, Lewis and Barraket) • Mapped citizens economic, social and political support networks (ego) • Primary Care Partnerships (Lewis and Baez) • Mapped strategic advice networks across 2 PCPs. • Crossing Boundaries (Alexander) • Mapped ‘local action’ network in Buloke Shire • DrinkWise (Lewis and Alexander) • Mapped connections between board members and industry • Climate change and health networks in Cambodia (Bowen et al) • Mapping formal and informal partnership ties between organisations

  10. Limitations/Pitfalls of SNA Research i) Data Collection problems ii) Clunky/cumbersome software iii) Tendency to be overly descriptive (good at what/when/where- less effective at how/why) iv) Structure/agency problem (underplays agency) *Works best with qualitative overlay

  11. Resources: Software: • Ucinet for Windows: Software for Social Network Analysis. (Borgatti, Everett and Freeman). (Includes NetDraw package) Free trial software at: https://sites.google.com/site/ucinetsoftware/home • Pajek (spider) by Vladimir Batagelj and Andrej Mrvar. Available for free at: http://pajek.imfm.si/doku.php?id=pajek Online Resources: • International Network for Social Network Analysis (INSNA) http://www.insna.org/ • Melnet http://www.sna.unimelb.edu.au/ Courses: • Malcolm Alexander, ‘Introduction to Social Network Research and Network Analysis’ (ACSPRI Short Course). Further information: http://www.acspri.org.au/node/995

  12. Further Reading: • Knoke, D., and Yang, S., (2008). Social Network Analysis. Thousand Oaks: SAGE Publications, Inc. • Charles Kadushin (2012) Understanding Social Networks: Concepts, Theories, and Findings. New York : Oxford University Press • Robert A. Hanneman and Mark Riddle (2005) Introduction to Social Network Methodshttp://faculty.ucr.edu/~hanneman/nettext/ • Granovetter, M. (1973) ‘The strength of weak ties’, American Journal of Sociology, 78, pp. 1360-80.

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