Introduction to Social Network Analysis by StuartSpruce

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									                   Introduction to
               Social Network Analysis

                   2009 Spring School on
                 Transition Studies in Tartu

Tetiana Kostiuchenko
PhD candidate (Aspirantura)
National University of
“Kyiv-Mohyla Academy”
 Background of social network analysis (SNA)
 Basic terms and concepts
 Centrality measures
 Visualization of network
Why to apply in transition /
transformation studies?
Because SNA approach allow not only to draw a
 ‘map of ties’ between structures/ institutions/
 societies as macro-level of social reality…
 … but, in addition, to track changes that occur with
  these ‘actors’ during social transformations in the
  contexts of interconnections at the micro-level
  (meaning connections between individuals,
  households or organizations)

                    Source: Knoke & Kuklinski “Network Analysis” (1982)
 What were the starting points?
Sociological and economic theories (Social
exchange theory, social and human capital)

Empirical researches
 (anthropology, psychology,
 corporate structure, markets)         SNA

 Mathematical modeling (graph
  theory, systems theory, neural
  networks, etc.)
Classical structural approach vs. SNA
Classical structural                   SNA =>
 approach =>                             relations between
attributes of actors                     actors

“Attributes are intrinsic               “Relation is …an
characteristics of people,      vs.     emergent property of
objects, or events” *                   the connection or
                                        linkage between units of
                                        observation” *

                        Source: Knoke & Kuklinski “Network Analysis” (1982)
Social network is...
  ... Model of material and non-material resources
       exchange in particular social group, community;

  ... ‘horizontal’ structure with interacting elements;
     (in contrast to the formal hierarchical structure of

  ... OR other empirical definition that comes from
       particular research needs, objects, units of analysis,
       researcher`s background, etc.
Methodological background:
mathematical modeling
• Graph theory
Leonard Euler (1736): Seven Bridges of Königsberg

                               B                    C

Methodological background:
graph theory
 • Graph is a collection of vertices and edges
   between them (the most convenient form of
  representing any ‘structure’)

                           Objects = vertices of the
                          graph/ nodes
                           Connections = edges that
                          connect pairs of vertices
                            Number of edges = size of
                          the graph
Methodological background:
measuring relations
• Sociometry (Moreno)
 measuring of social relationships through ‘emotional’ ties,
  reciprocated ‘likes’ and ‘dislikes’ within a small group
                Sociometric matrix                Sociogram
Types of relations            Types of actors
   Transactions               individuals (people)
   Communication              organizations
   (information exchange)     households
   Boundary penetration
   (affiliation)              words
   Instrumental (getting a    countries and
   job);                      etc...
   Sentiment (affection,
   admiration, or hostility
   toward each other)
   Authority/power (issuing
   and obeying commands)
  -Different types of relations identify different networks,
  even when imposed on the identical set of elements;

  - Relations can be measured through :

  1) intensity, or strength,             2) level of joint
  of the link between two                involvement in
  actors                                 the same activities
  (i.e. volume of transacted resource;
  frequency of transactions)
Network structure
            DIRECTED                                UNDIRECTED


        COMPLETE NETWORK:                      INCOMPLETE NETWORK:
     information about                            information about
  patterning of ties among                     patterning of ties among
         ALL actors                             some actors is absent
                                                (existence of isolates)
Types of network structures
                     HIGH                  LOW
“Path”, “trail”, AND “walk”
• Path: do not repeat nodes                     10
  ▫ 1-2-3-4-5-6-7-8                                              12

  ▫ NOT 7-1-2-3-7-4                    11
• Trail: do not repeat edges
  ▫ 1-2-3-1-7-8                        2
  ▫ NOT 7-1-2-7-1-4
• Walk: without limits

  ▫ 1-2-3-1-2-7-1-7-1
                                   4                     5
 Basic measures for the analysis
  • Size of the network (the number of existing connections)
  • Density (the number of ties divided by the number of pairs, times 100)
  • Centrality measures
             - degree               Degree: Direct connections to other
                                       actors, higher scores are considered
             - closeness               as better
                                    Closeness: farness from neighbors, the
Path-based - betweeness                lowest scores mean being closer
                                      Betweeness:«gatekeepers» who
                                         connect subgroups, clusters; higher
                                         scores means that if to remove this
Walk-based => eigenvector                node, the segments will probably be
                                      Eigenvector: «popularity» through being
                                         connected with well-connected




                      Data courtesy of David Krackhardt (the example from
                      UCINET software package)
Interlocking Directorates in the Corporate Community
by G. William Domhoff
Political Elite Network: ALL types of ties
Applications of SNA approach in
different disciplines
                 Sociology     Anthropology


                                       Political Science


                 Criminology                  еtc…
... and in particular:
 “Buzzing” in marketing
 Organizational network analysis and
 Diffusion of innovations
 Interlocking directorates and elite interlocks…
Well-known ‘networkers’:
Mark Granovetter (Stanford University), who argued and
empirically demonstrated that economic action is necessarily
embedded in the world of social relations and connections
David Knoke (University of Minnesota). Together with James
H.Kuklinski, he published the work on SNA cited above, “Network
Analysis” (1982)
Barry Wellman (University of Toronto). The author of one of the
basic works on SNA statistical procedures – “Network Analysis: some
basic principles” (1983)
Stanley Wasserman – професор психології, статистики та
соціології. Разом із K.Faust написав фундаментальну книгу з
методології соціальних мереж “Social Network Analysis” (1994)
… and plenty of others (mostly from the USA and the EU)
Publications on SNA theory, methodology and
empirical applications can be found at ...
  INSNA (International Network of Social Network
  Analysis). Founded 1978.
Official web-page is
  Connections and Social Networks journals
  Summer schools in SNA:
- Essex University Summer School in Data Analysis and Collection (UK)
- ECPR Summer School in methods and techniques (Ljubljuana , Slovenia)
  UCINET & NetDraw
is developed by Steve Borgatti (Boston college) and
Martin Everett (University of Manchester) , – 1 month free-of-charge
 trial version is available

  Pajek (for Large Network Analysis) is developed
 by Vladimir Batagelj and Andrej Mrvar(Ljubljana, Slovenia) – free-of-charge

   InFlow – mostly used for the organizational network analysis
is developed by Valdis Krebs (Cleveland, Ohio)

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