Social Network Analysis
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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.

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

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Social Network Analysis Social Network Analysis Presentation Transcript

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