Social Networks Theory and Analysis Graduate Seminar SS 241B 69614 Fall 1997 "Network Theories of Social Structure" Professor Douglas R. White
Proseminar in Social Networks; Introduction to Network Theory and Methods for 1. Social History (AIPIF Modernity's History students) 2. GSM 3. Social Ecology 4. Social Sciences
This seminar provides an overview of social network analysis, theories and methods, and their applicability to social science disciplines such as sociology, anthropology, social history and social demography. This year focuses on a "hands-on" approach using standard network analysis software to analyze data from one's own project(s), exercises of the W&F textbook and exercises related through the additional readings to each subject presented, as discussed by the participants.
Students should have or gain access to UCINET, KRACKPLOT and PGRAPH (IBM compatible PC programs) through the internet or our SST computer labs, and be able to edit their datasets as ASCII text (standard word processor option).
ANTICIPATED CLASS SCHEDULE
SESSION ONE: Introduction to Structural AnalysisLecturer: Doug White Contents: Revision of the structuralist/functionalist discussion; the structuralism of Levi-Strauss; structure in social networks; from social groups to social networks and back again; networks, groups, roles, rules, norms and sanctions, institutions, activities.
----- break -----Discussion about the organization of sessions Four to Ten. Teams of two students will prepare one chapter (or section of a chapter, depending on the length and/or difficulty of the subject) to be presented and discussed at the seminar. Presentations should include examples and solution to exercises from the book or from other sources. The class is expected to attend each one of the sessions, to do the same readings as the lecturers in order to make comments and raise questions about the subject in turn, and to do the exercise for each session as homework from one week to the next. Overview of UCINET data entry and analyses. How to code a network, how to edit, sort and manipulate files in and out of UCINET. Exercise: Prepare a network dataset in a form for UCINET analysis. Assignment (readings for following week): Wasserman & Faust, Chapters 1 and 2 Berkowitz & Wellman (1988), Introduction Scott (1992), Chapters 1-3
SESSION TWO: An Overview of Social Network AnalysisLecturer: Doug White Contents: Discussion about the readings: Is network analysis a compound of techniques (Scott); is it an array of methods grounded on its own theoretical stance? (W&F). Is it a comprehensive or a specialized approach? Is network theory formal, substantive or both? What is the debate over grounded theory?
----- break -----History of social network analysis; theoretical motivations; types of networks (whole networks, ego-centered, kinship networks); the tie- strength issue; network data collection. Introduction to defining variables in different notational formats. Exercises (for following week): 1) Specify a series of raw variables (individual and group level characteristics, relational characteristics, context variables) and a set of finished variables (network properties at the level of individual, group, and network characteristics) that you will use in the analysis of your data using your own computations or UCINET or other program packages; 2) translations from one notation to another, with examples taken from the readings and from your own dataset. Assignment: W&F, Chapter 3 Freeman, White & Romney (1989), Chapter 1
SESSION THREE: Network Analysis: An Introduction to Formal Definitions and Notation.Lecturer: Doug White Contents: Graph theoretic, sociometric and algebraic notations. Their uses in network analysis.
----- break -----Introduction to Centrality Concepts Exercises: Compute pairwise dependencies; betweenness, closeness and degree centralities and centralization 1) with data provided by the lecturers, who should explain the method they used to obtain the data and the techniques they applied to do the analysis, and 2) on your dataset and examples taken from the readings. Assignment: W&F, Chapter 5 (Chapter 4 on Graph Theory goes to John's course) Freeman, The Gatekeeper Freeman et al., Centrality II
SESSION FOUR: Centrality Concepts and MeasuresLecturers: Silvia Casasola and Christine Avenarius Contents: Definitions of actor centrality and graph centralization; degree (actor) centrality and (graph) centralization; betweenness (actor) centrality and (graph) centralization; closeness (actor) centrality and (graph) centralization. How the latter two are derived from pairwise dependencies (see "Gatekeeper"). Examples of each one.
----- break -----General discussion and comments. Exercise: on balance and transitivity with data provided by the lecturers. General discussion and comments. Assignment: W&F, Chapter 6 Cartwright & Harary (1979) (Davis article on balance, clusterability and transitivity)
SESSION FIVE: Balance, Clusterability and TransitivityLecturers: Ben Jester and Eric Widmer Contents: Heider's idea of balance; formal definitions: balance in signed graphs; clusterability and transitivity in digraphs. Examples.
----- break -----Exercise: Assignment: W&F, Chapter 7 (and student selected article about cohesive subgroups)
SESSION SIX: Cohesive SubgroupsLecturers: William Fitzgerald and Ti-Lien Hsia Contents: The notion of social cohesion; theoretical motivations of identifying social subgroups; network formalization of subgroups; cliques (n-cliques, n-clans, n-clubs, k-plexes, k-cores, lambda sets).
----- break -----Graph theoretic and other approaches to represent cohesive subgroups (MDS, matrix permutation, factor analysis), including examples with data provided by the lecturers. General discussion and comments. Exercise: Assignment: W&F, Chapter 8 (pp.291-312) Freeman & White (1993) about Galois lattices
SESSION SEVEN: Affiliation NetworksLecturers: Jim Hess and Narda Alcantara Valverde Contents: Two-mode networks, theoretical motivations and background; representation of two-mode networks: affiliation matrices, bipartite graphs, hypergraphs, simplicial complexes. Examples from the book or any other source.
----- break -----Exercises: 1) on affiliation networks with data provided by the lecturers and from one's own dataset; 2) Analyze a part of the affiliation network as a Galois lattice. Assignment: W&F, Chapter 8 (pp.312-343)
SESSION EIGHT: Affiliation NetworksLecturers: Bret Breslin and Jeff Stern (if he wants to attend) Contents: Co-membership of actors and overlapping of events; properties of actors and events (rate of participation, size of events, density, reachability, connectedness, diameter). Example from the book (Galazkiewiz CEO's).
----- break -----General discussion and comments. Galois lattices: an accurate model of a social system. Example with the Davis, Gardner and Gardner (1941) data. Exercises: 1) Create a kinship dataset from raw data, analyze with p- graph; 2) learning to read P-Graphs; finding patterns of re-linking and other properties on data provided by the lecturers (and/or the professor); 3) Apply principles of balance theory and clusterability to the kinship network. Assignment: Chapters 1-3 in Schweizer and White (1997) White (1997) article in M.I.S.H. Literature about the P-Graph Harary & White (1997)
SESSION NINE: Kinship and "Matching" Systems as NetworksLecturers: Pat Skyhorse and Silvia Casasola (and/or Rick/Eric, if they wish...) Contents: Kinship systems and their importance as indicators of social structure; definitions of re-linking and structural endogamy, and other relevant properties of P-Graphs. Other "matching" structures for incorporation into p-graphs: people/jobs, people/corporations, padres/compadres, etc. Examples (Pul Eliya, the Tory Islanders, the Austrian Village, the Tlaxcalan compadrazgo study). Click for larger Image (39K)
----- break -----Exercise and Readings: None (by this time of the quarter everyone will be overwhelmed by TAships and papers for other courses).
SESSION TEN : free for subjects lagging behind, for general discussion and/or issues raised by the participants (or for the Lion to roar).Party: Happy New Year.