Social Network Analysis

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Slides from a talk on Social Network Analysis I gave to Diane Kelly's PhD research methods class.

Social Network Analysis

  1. 1. Social Network Analysis<br />Fred Stutzman<br />
  2. 2. Overview<br />General Introduction<br />Disciplinary perspectives<br />Terms and Definitions<br />Elements of a social network<br />Analytic Techniques<br />Data collection, software<br />Basic Analysis<br />Descriptive measures<br />Advanced Analysis<br />Block Models, ERGM’s<br />
  3. 3. The Social Network Perspective<br />What is a social network?<br />Wasserman and Faust: “The social network perspective encompasses theories, models and applications that are expressed in terms of relational concepts and processes. That is, relations defined by linkages among units are a fundamental component…” <br />Wellman and Giulia: “Social network analysis treats personal communities as networks whose composition, structure, and contents are defined from the standpoint of (a usually large sample of) focal individuals at their centers.” <br />Burt: “Network models describe the structure of one or more networks of relations within a system of actors.”<br />
  4. 4. The Social Network Perspective<br />Personal Networks<br />Ego-centric networks defined at the individual level<br />Behavioral Networks<br />Networks as represented in activity, socio-technical systems<br />Organizational Networks<br />Networked relations between macro-level structures<br />Online Social Networks<br />Publicly articulated networks as represented in systems<br />
  5. 5. Fundamental Concepts<br />Elements of a Social Network<br />Actor: Actors are discrete individual, corporate, or collective social units (among others; also: node, vertex)<br />Individual: A Facebook friend, a romantic partner<br />Corporate: Companies, government agencies, universities<br />Collective social units: Groups that can be represented as a node on a graph<br />The actor represents the tie-generating unitand is therefore flexibly interpretable<br />Quoting (Wasserman & Faust, 1994)<br />
  6. 6. Fundamental Concepts<br />Elements of a Social Network<br />Relational Tie – Can be directional, weighted (also: line, arc, edge)<br />Liking or friendships<br />Transfer of resources<br />Association or affiliation<br />Behavioral interaction<br />Movement between places<br />Physical connection<br />Formal relations<br />Biological relationship<br />Quoting (Wasserman & Faust, 1994)<br />
  7. 7. Fundamental Concepts<br />Complex ties<br />Edge: Undirected line<br />Arc: Directed line<br />Loop: Line that ties vertex to self<br />Multiple: Directed arc occurring multiple times<br />Graph types<br />Simple undirected graph: No directional ties, loops, multiple lines<br />Simple graph: No multiple lines<br />Network: Complex graph<br />
  8. 8. Fundamental Concepts<br />Elements of a Social Network<br />Groupings – The power of network analysis lies in the ability of model relationships among systems of actors<br />Dyad: Relationship btw/ 2 actors<br />Triad: Three actors and potential ties within<br />Subgroups: Larger groupings of actors within the network<br />Groups: Finite collections ofactors<br />Partitions: Collections assignedcategorical value<br />Quoting (Wasserman & Faust, 1994)<br />
  9. 9. Elements of a Social Network<br />The social network represents the finite sets of actors and the relations defined between them<br />Actors<br />Ties<br />Groupings<br />What kind of questions can we ask of social network data?<br />Quoting (Wasserman & Faust, 1994)<br />
  10. 10. Types of Social Networks<br />One-mode network: Relations between a single set of actors <br />Marriage networks between people<br />Transactions between companies<br />Movement between places<br />Two-mode network: Relations between two sets of actors<br />Donor relationships between corporations and organizations<br />Two-mode network: Affiliation network (one actor/one event)<br />Memberships in clubs <br />Participation on a board of directors<br />Quoting (Wasserman & Faust, 1994)<br />
  11. 11. Types of Social Networks<br />Ego-centric or “personal” networks<br />A network with a focal actor (the “ego”) and “alters” who have connections to the ego<br />Bearman/Moody study: Sexual relations w/alters<br />General Social Survey: “From time to time, most people discuss important matters with other people.  Looking back over the last six months who are the people with whom you discussed matters that are important to you?<br />Fischer: Relationship between geographical setting and support provided by the network<br />Gulia and Wellman: Supportive nature of ‘net contacts<br />Ellison, Steinfeld and Lampe: Socially supportive outcomes of Facebook use<br />Quoting (Wasserman & Faust, 1994)<br />
  12. 12. Analytic Techniques<br />How to collect social network data?<br />Personal network questionnaires<br />Position generators<br />Administrative records<br />Organizational charts<br />Secondary analysis<br />Socio-technical systems<br />
  13. 13. Analytic Techniques<br />What does SNA data look like?<br />Edge lists<br />[1,2<br /> 1,3<br /> 3,2]<br />Adjacency matrix (symmetric)<br />
  14. 14. Analytic Techniques<br />Software for Analysis<br />Large number of software packages available for SNA <br />Popular packages<br />Pajek: http://vlado.fmf.uni-lj.si/pub/networks/pajek/<br />UCINet: http://www.analytictech.com/ucinet/<br />Gephi: http://gephi.org/<br />Also: ORA, NodeXL, Network Workbench<br />Advanced packages<br />Statnet and iGraph packages in R (highly recommended): http://csde.washington.edu/statnet/<br />JUNG, NetworkX (Libraries for Java and Ruby, C++ Lib?)<br />Web tools<br />Many Eyes http://manyeyes.alphaworks.ibm.com/manyeyes/<br />
  15. 15. Analyzing a Social Network<br />Basic properties of social networks<br />Descriptive statistics: How many actors, how many ties?<br />Degree centrality: How many ties does each actor have; what kinds of actors have lots of ties, few ties. <br />Are more ties always better?<br />Betweenness centrality: The connective properties of actors, hubs and authorities<br />Better to connect two disparate groups?<br />Closeness centrality: Path length between actors<br />Better to be closer to some people?<br />Network centrality: Average path length to traverse a network<br />Shorter paths better?<br />Quoting (Wasserman & Faust, 1994)<br />
  16. 16. Network properties<br />Descriptive: How many actors, ties; Degree centrality: How many ties on average;Betweenness: How connective; Closeness centrality: Path length between; Network<br />Centrality: Avg path length of the network<br />Quoting (Wasserman & Faust, 1994)<br />
  17. 17. Advanced Analysis<br />Block Modeling<br />Examines the relations between classes of vertices (nodes)<br />Explores and compares the connective properties of classes, exploring density patterns<br />Two approaches: Random start and Optimized<br />Amenable to hypothesis testing with the bootstrap<br />
  18. 18. Advanced Techniques<br />Random Graph Comparison<br />Allows for tests of the associational aspects of categories (partitions), compared to exponential random graph<br />CDF of tie 0->1, Binomial dist<br />Amenable to MLE, though computationally intensive<br />MCMC Simulation <br />Modeled as log-odds<br />Statnet in R<br />
  19. 19. The Personal Network<br />Summarizing the social network<br />Components: Actors, Ties, Relationships and Groups <br />Modes: One-Mode, Two-Mode<br />Measures: How many connections, who has the important connections, how dense is the network?<br />Instruments: Name generators, position generators, scales<br />Outcomes: Social support, social capital, and a host of others.<br />Why is the personal network important?<br />
  20. 20. “Classic” SNA Studies<br />Bearman, P. S., Moody, J., and Stovel, K. (2004). Chains of Affection: The Structure of Adolescent Romantic and Sexual Networks. American Journal of Sociology, 110(1), 44--91.<br />Padgett, J. and Ansell, C. K. (1993). Robust Action and the Rise of the Medici. American Journal of Sociology, 98(6), 1259--1319. <br />Framingham Heart Study in Christakis, N. and Fowler, J. (2009). Connected: The Surprising Power of Our Social Networks and How They Shape Our Lives. New York, NY: Little Brown and Co.<br />Wellman’s East York Studies, Fischer’s Personal Networks in Cities and Towns<br />Adamic, L., Buyukkokten, O., and Adar, E. (2003). A Social Network Caught in the Web. First Monday, 8(6). <br />
  21. 21. Resources<br />Useful Mailing Lists<br />SOCNET <br />CITASA (ASA)<br />Websites<br />INSNA: http://www.insna.org/<br />SUNBELT Conference: http://www.insna.org/sunbelt/<br />Recommended Texts<br />De Nooy’s et al.’s Pajek text<br />Wasserman and Faust’s Social Network Analysis<br />Easley and Kleinberg’s Networks, Crowds and Markets<br />

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