Soc 229 Seminar on Social Networks

Professor: James Moody

 

 

Meeting Time: T Th, 1:15 – 2:30

Office Hours: Th 3:00 – 4:30

Place:  Social Sciences 229

 

“To speak of social life is to speak of the association between people – their associating in work and in play, in love and in war, to trade or to worship, to help or to hinder.  It is in the social relations men establish that their interests find expression and their desires become realized.”

                                                                                    -- Peter M. Blau, 1964

 

 

Overview:

This seminar focuses on theoretical and substantive themes within social network analysis.  The theoretical heart of this approach to social science is that actors are interdependent, and that social structure emerges from regularities in this interdependence.  In this seminar, we will couple the substantive and theoretical development of social network analysis with methodological tools to implement network research.  By the end of the course, you should (1) know the major theoretical ideas supporting network research, (2) be able to collect social network data and, (3) be able to analyze and interpret social network data. 

 

Social network research is unique in the extent to which methodological tools derive directly from substantive theories.  As such, class time will be split almost 50-50 on methodological and substantive (theory, application, and examples) issues, with each substantive topic tied to a new method or analysis strategy.  Substantive topics will include work on sexual behavior, organizational performance, delinquency, power, friendship, and much more.

 

 

Requirements:

The main requirement of this seminar is a research paper that uses the methods or ideas of social network analysis.  This may be a revision of previous work (an MA paper, another course paper, etc.) or a new paper.   If this is a revision of a previous paper, you need to show that the addition of network ideas or methods significantly contributes to the revision.  You may collaborate with up to 2 other students (3-authors total) on your final paper.  The second requirement for the class is a set of homework assignments designed to build familiarity with the software and analysis techniques.  Assignments are self-graded with the solutions posted on the course webpage, they are due the next class day (so an assignment listed on class 2 is due on class 3).  Finally, since this is a seminar, in-class participation is necessary. 

 

Texts:

The main texts for the class are

-          Wasserman and Faust (1994): Social Network Analysis. Cambridge University Press.  This book will provide the main methodological and background reading for the course.  

-          Kadushin, Charles (2010): Making Connections: An introduction to social network theory, concepts and findings.  This is a great “what and why” book – not a “how to” book, particularly for students with little social networks background.

-          Martin, John Levi (2009): Social Structures.  This is a theory book on how types of relations constrain/construct types of aggregate social structures.

 

As background, you may also want to review:

-          Barabasi, Albert-László Linked: The New Science of Networks.  Provides an overview from the point of view of physicists, who have recently started thinking about networks (and social networks as part of that).

-          Freeman, Linton. The Development of Social Network Analysis by Linton Freeman.

 

Most papers we are reading will be linked to on-line sources from the class web-page version of this syllabus.  Any that we cannot get on-line will be available for copy in a folder outside my office door.

 

Software:

I will provide sample code, instruction and so forth in a number of software programs.  The main ones are:

 

1)       UCI-NET.  This is the industry standard network analysis program.  The most recent version is available for about $40 from Analytic technologies. Orders may be placed by web, mail, telephone, fax, or e-mail.   Web: www.analytictech.com.  E-mail: sales@analytictech.com

 

2)       Access to SAS, including IML, and a set of programs I have written called SPAN (Sas Programs for Analyzing Networks), which contains a set of useful routines.  The SPAN program is free, and can be downloaded from the data page of the class website.  This is the main software source I will instruct in.

 

3)       PAJEK.  A program for analyzing and visualizing large networks. It is free.  You can download the most recent version of PAJEK at: http://vlado.fmf.uni-lj.si/pub/networks/pajek/default.htm.  A good book on the “how to” of PAJEK is Exploratory Network Analysis With PAJEK, Cambridge Press

 

4)       R.  The R platform is necessary for the statistical models of networks we will be exploring, but can also be used as a general network analysis program.  I will provide hints at how to do general analysis in R and more detailed examples for the statistical modeling projects.  For those who like to program in R, the main modules to review are “SNA” (Carter Butts), “Statnet” (Handcock et al), and iGraph (Csardi).  R is free.

 

5)       Other sundry programs:

There are many drawing programs (yEd, VisOne, SoNIA) that have neat tricks, ORA is a general-purpose program with lots of tools.  You are welcome to use any of these.

 

Online resources

1)      Class web page.  This is where the most up-to-date version of the syllabus will always be, and links to all of the course material.   http://www.soc.duke.edu/~jmoody77/s884/index.htm 

2)      International Network for Social Network Analysis (INSNA) home page http://www.insna.org/


Schedule:

Class 1: Introduction to Social Network Analysis

Summary: First day of class.  Discuss syllabus, go over the history of social network research, general trends in the field and some basic elements of how social network data differ from data social scientists are used to collecting.

Reading:

Kadushin, Intro & Chapter 1.

Borgatti, S.P et al “Network Analysis in the Social SciencesScience 323, 892 (2009).

Butts, Carter T. “Revisiting the Foundations of Network Analysis Science 325, 414 (2009)

Assignments: Family as Social Network & Substantive implications

Recommended /Background Reading:

Barabási, Albert-László Linked: The New Science of Networks

Freeman, Linton The Development of Social Network Analysis by Linton Freeman

Use of family network size estimates:

Gartner, Scott.  2009. “Ties to the Dead: Connections to Iraq War and 9/11 Casualties and Disapproval of the President” American Sociological Review

Moody, James. “Fighting a Hydra: A Note on the Network Embeddedness of the War on Terror”, Structure and Dynamics: eJournal of Anthropological and Related Sciences: 1(2): Article 9.

Any number of reviews of network science, see for example SCIENCE VOL 325.

 

Class 2.  Foundations of network analysis

Summary: Continue discussion of network theory elements, describe data structures, distinctions between directed, undirected, valued, local and global networks, introduction to software & graph drawing.

      Reading:

Wasserman & Faust, Chapter 1 & 2 (focus on 1st half of chap 2).

Kadushin, Chapter 2 & Chapter 3

Martin, J. Front matter & Chapter 1.

Emirbayer, M. 1997. "Manifesto for Relational Sociology." American Journal of Sociology 103:281-317.

            Assignments: Matrix manipulations, graph translation exercise, network drawing.

Recommended /Background Reading:

Borgatti, S.P. “A quorum of graph theoretic concepts”

Wellman, Barry: “Structural Analysis: From method and metaphor to theory and substance”

           

Class 3.  Collecting Network Data

Summary: What are the best ways to collect network data? What are the tradeoffs involved in different network data designs, how does data collection quality affect results? How do we collect data in ethically responsible ways?

            Reading:

                  Main:

Breiger, Ronald L. 2005. “Introduction to special issue: ethical dilemmas in social network research  Social Networks p89-93

Klovdahl, Alden S. 2005.Social network research and human subjects protection: Towards more effective infectious disease controlSocial Networks p119-137

Katushin, C. Chapter 10

Marsden, P.V. 1990. Network data and measurement.” Annual Review of Sociology 16:435-63

Bearman & ParigiCloning Headless Frogs and Other Important Matters: Conversation Topics and Network Structure  Social Forces

Borgatti : http://www.analytictech.com/networks/data.htm

             Assignments:  Take & evaluate a network survey.

Background Reading:

Bell, D. C. et al “Partner naming and forgetting: Recall of network membersSocial Networks p279-299

Bernard, W. H., P. Killworth, and L. Sailer. 1979. “Informant accuracy in social networks. Part IV: A comparison of clique-level structure in behavioral and cognitive network data.” Social Networks 2: 191-218.

Butts.  2003. “Network inference, error and informant (in)accuracy: a Bayesian approach,” Social Networks 25:2: 103-140. 

Eagle, N. A. Pentland, and D. Lazer (2009), "Inferring Social Network Structure using Mobile Phone Data", Proceedings of the National Academy of Sciences (PNAS) (to appear).

Faust, K. 2009. “Triadic configurations in limited choice sociometric networks: Empirical and theoretical resultsSocial Networks

Freeman, L. A.K. Romney, S.C. Freeman. 1989. “Cognitive Structure and Informant Accuracy,” American Anthropologist 89.

Kadushin, C. “Who benefits from network analysis: ethics of social network researchSocial Networks p139-153

Killworth, P.D and H. R. Bernard. 1976. “Informant accuracy in social network data,” Human Organization 35(8): 269-286.

Marsden. PV 1990. “Network data and measurement,” Annual Review of Sociology 16: 435-463.

Vehovar, V et al “Measuring ego-centered social networks on the web: Questionnaire design issuesSocial Networks  p213-222

 

Class 4.  Local Networks I: Network Composition & Population Mixing

Summary: The building blocks of a network are the sets of relations each person is embedded within.  Today we discuss how positions can be defined in terms of the pattern and composition of network alters.  We identify sources of such data in the literature and how to manipulate them.

            Reading: 

McPherson, Smith-Lovin, BrashearsSocial isolation in America: Changes in Core Discussion Networks over Two DecadesAmerican Sociological Review

Fischer, CS (2009) “Comment: The 2004 GSS Finding of Shrunken Social Networks: An Artifact?” Claude S. Fischer American Sociological Review

McPherson, Smith-Lovin, Brashears  (2009) “Reply: Models and Marginals: Using Survey Evidence to Study Social Networks” (ASR)

Fischer, Claude: To Dwell Among Friends, Chapters 3, 8, 9, 12, 14 (don’t worry, they are short and easy!)

Cornwell, B., Laumann, E.O. and Schumm. 2009. “The Social Connectedness of Older Adults: A National ProfileAmerican Sociological Review

 

Assignments: Ego-Network Characteristics.

            Background Reading:             

Bidar, Clair “Evolutions of personal networks and life eventsSocial Networks p359-376

Kalmijn, M et alHomogeneity of social networks by age and marital status: A multilevel analysis of ego-centered networksSocial Networks p25-43

Lizardo, Omar ()How Cultural Tastes Shape Personal Networks” American Sociological Review

Marsden, Peter: “Core discussion networks of Americans”

Martin, J.L. “Persistence of close personal ties over a 12-year periodSocial Networks p331-362

Mizruchi, Mark & Linda Brewster Stearns Getting Deals Done: The Use of Social Networks in Bank Decision-MakingAmerican Sociological Review 2001 66:647-671

Moore, G. 1990. "Structural Determinants of Men's and Women's Personal Networks." American Sociological Review 55:726-35.

Renzulli, L. A., H. Aldrich, and J. Moody. 2000. "Family Matters: Gender, Networks, and Entrepreneurial Outcomes." Social Forces.

Van Der Gaag, Martin & Tom SnijdersThe Resource Generator: social capital quantification with concrete itemsp1-29  Social Networks

van Duijn, M. A. J., J. T. ban Busschbach, and T. A. B. Snijders. 1999. "Multilevel Analysis of Personal Networks As Dependent Variables." Social Networks 21:187-209.

Wellman, B. and S. Wortley. 1990. "Different Strokes From Different Folks: Community Ties and Social Support." American Journal of Sociology 96:558-88.

Wellman, B., R. Y. Wong, D. Tindall, and N. Nazer. 1997. "A Decade of Network Change: Turnover, Persistence and Stability in Personal Communities." Social Networks 19(1):27-50.

 

(There are hosts of other good pieces using local networks.  Most articles in the health field, for example, use local networks, since the data are easy to collect).

 

Class 5. Local Networks II: Patterns

Summary: The structural patterns in local networks affect the distribution of information and power in that network.  Today we focus on identifying the effects of local network configurations and how those configurations fit into wider patterns of relations.

Reading:

Burt, R.  Structural Holes, Chapter 1 (skim chapter 2).

Burt, R. 2004.  “Structural Holes and Good IdeasAmerican Journal of Sociology 110:349-400

Granovetter, Mark. 1973. "The Strength of Weak Ties." American Journal of Sociology 78:1360-80.

 (plus the chapters from Fischer on patterns & density)

            Assignments: Selecting Ego-networks from global networks, Structural Hole measures.

Background Reading:

Buskens, V & van de Rijt, Arnout “Dynamics of Networks if Everyone Strives for Structural Holes” American Journal of Sociology

Cornwell, B. () “Good health and the bridging of structural holesSocial Networks p92-103

Cowan, Robin &  Nicolas Jonard. (2007) “Structural holes, innovation and the distribution of ideas.” Journal of Economic Interaction and Coordination 2:2, 93-110

Everett & Borgatti (19xx) “Ego network betweennessSocial Networks p31-38

Fernandez-Mateo, Isabel () “Who Pays the Price of Brokerage? Transferring Constraint through Price Setting in the Staffing Sector” American Sociological Review

Granovetter, Mark. (1974) Getting a job; a study of contacts and careers.   Harvard University Press

Kalish & Robins. () “Psychological predispositions and network structure: The relationship between individual predispositions, structural holes and network closure” Social Networks p56-84

Lee, Nancy Howell (1969) The search for an abortionist.  University of Chicago Press

Tiwana, Amrit. (2008) “Do bridging ties complement strong ties? An empirical examination of alliance ambidexterity.” Strategic Management Journal 29:3,251-272

 

Class 6. Social Capital

Summary: A large body of network-relevant work centers on the idea of social capital.  Here we review network approaches to that work.

Reading:

James Moody and Pamela Paxton. 2009. “Building Bridges: Linking Social Capital and Social Networks to Improve Theory and Research.American Behavioral Scientist 52: 1491-1506. [intro to 2-volume ABS special issue on social capital and networks; review some of the other papers for substance]

Coleman, J. 1988.  Social Capital in the Creation of Human Capital  American Journal of Sociology 95: 95-120

Assignments: Social Capital Inventory Items

            Background Reading:

This is an exceedingly large literature; see the bibs in the special issue above for classics…

Putnam Bowling Alone

McFarland, D & RJ Thomas. 2008. Bowling Young: How Youth Voluntary Associations Influence Adult Political Participation  American Sociological Review

Lin, Cook & Burt 2001.  Social Capital: Theory & Research (intro chapter)

 

 

Class 7. Relations through associations

Summary: People form relations through overlapping associations.  In so doing, they not only create a network of people, but also a network of associations.  This is captured through the duality of persons and groups, and provides a very powerful way to identify network processes through commonly available data.

Reading:

Breiger, R. L. 1974. "The Duality of Persons and Groups." Social Forces 53:181-90.

Moody, James. 2004. “The Structure of a Social Science Collaboration Network” American Sociological Review 69:213-264 (skim, will present)

Burris, Val () “Interlocking Directorates and Political Cohesion among Corporate Elites”AJS

W&F Chapter 8 (skim).

Assignments: Constructing a dual (person-through-group) network.

            Background Reading:

Baldassarri, D and Mario Diani. (2007) The Integrative Power of Civic Networks. American Journal of Sociology 113:3, 735-780

Bearman, P. and K. Everett. 1993. "The Structure of Social Protest." Social Networks 15:171-200.

Frank, K. et. al () “The Social Dynamics of Mathematics Coursetaking in High School”AJS

 

Class 8.  Centrality.

Summary: Another conception of “position” in a social network deals with where an actor resides within a network.   Falling under the broad heading of centrality, a series of measures are identified that highlight individuals positions in the network.

            Reading:

W&F Chap. 5.

Bonacich, P. 1987. "Power and Centrality: A Family of Measures." American Journal of Sociology 92:1170-1182.

Borgatti & Everett. 2006. “A Graph-theoretic perspective on centrality” p466-484 Social Networks

Borgatti, S. P. 2005. “Centrality and network flow” Social Networks p55-71

Plus one of the Substantive readings using centrality from class 9.

Assignments: Calculate and compare different measures of centrality on the same network.

            Background Reading:

Bell, D. C., J. S. Atkinson, and J. W. Carlson. 1999. "Centrality Measures for Disease Transmission Networks." Social Networks 21:1-21.

Bolland, J. M. 1988. "Sorting Out Centrality: An Analysis of the Performance of Four Centrality Models In Real and Simulated Networks." Social Networks 10:233-53.

Freeman, L. C. 1977. "A Set of Measures of Centrality Based on Betweenness." Sociometry 40:35-41.

———. 1978-1979. "Centrality in Social Networks." Social Networks 1:215-39.

Friedkin, N. E. 1991. "Theoretical Foundations for Centrality Measures." American Journal of Sociology 96:1478-504.

Rothenberg, R. B., J. J. Potterat, W. W. Woodhouse, S. Q. Darrow, S. Q. Muth, and A. S. Klovdahl. 1995. "Choosing a Centrality Measure: Epidemiologic Correlates in the Colorado Springs Study of Social Networks." Social Networks: Special Edition on Social Networks and Infectious Disease: HIV/AIDS 17:273-97.

 

Class 9.  Centrality

Summary: Continue our work on centrality, focusing on processes of information and disease diffusion.

            Reading:

Friedkin, N. E. 1993. "Structural Basis of Interpersonal Influence in Groups: A Longitudinal Case Study." American Sociological Review 58:861-72.

or

Baker, W. E. and R. R. Faulkner. 1993. "The Social Organization of Conspiracy: Illegal Networks in the Heavy Electrical Equipment Industry." American Sociological Review 58:837-60.

Assignments:

            Background Reading:

Bell, D. C., J. S. Atkinson, and J. W. Carlson. 1999. "Centrality Measures for Disease Transmission Networks." Social Networks 21:1-21.

Bolland, J. M. 1988. "Sorting Out Centrality: An Analysis of the Performance of Four Centrality Models In Real and Simulated Networks." Social Networks 10:233-53.

Bonacich, P. 1987. "Power and Centrality: A Family of Measures." American Journal of Sociology 92:1170-1182.

Brandes, U “On variants of shortest-path betweenness centrality and their generic computation” Social Networks p.36-145

Clifton, Allan. Eric Turkheimer, Thomas F. Oltmanns () “Personality disorder in social networks: Network position as a marker of interpersonal dysfunction Social Networks” Pages 26-32

Freeman, L. C. . 1978-1979. "Centrality in Social Networks." Social Networks 1:215-39.

Freeman, L. C. 1977. "A Set of Measures of Centrality Based on Betweenness." Sociometry 40:35-41.

Friedkin, N. E. 1991. "Theoretical Foundations for Centrality Measures." American Journal of Sociology 96:1478-504.

Kolaczyk, E.D David B. Chua, Marc Barthélemy  Group betweenness and co-betweenness: Inter-related notions of coalition centrality” Social Networks p190-203

Rothenberg, R. B., J. J. Potterat, W. W. Woodhouse, S. Q. Darrow, S. Q. Muth, and A. S. Klovdahl. 1995. "Choosing a Centrality Measure: Epidemiologic Correlates in the Colorado Springs Study of Social Networks." Social Networks: Special Edition on Social Networks and Infectious Disease: HIV/AIDS 17:273-97.

Zemljič, Barbara & Valentina Hlebec () “Reliability of measures of centrality and prominence” Social Networks p73-88

 

Class 10.   Building Nets from Local Action 1: Social Balance.

Summary: We have now seek the basic structures of informal networks and details of local networks.  What interpersonal process could be consistent with both of these features?  More important, can we identify a local level mechanism that would generate such structures? Will also introduce the problem of statistical measurement of network attributes.

Reading:

 Martin, J. Social Structures Have (have book finished by now)

 Davis, J. A. 1963. "Structural Balance, Mechanical Solidarity, and Interpersonal Relations." American Journal of Sociology 68:444-62.

W&F chap 6 & 14 (skim 14)

Gould, Rodger (2002). “The Origins of Status Hierarchies: A formal theory and Empirical Test.” American Journal of Sociology. 107:1143-1178

            Assignments: Identify transitivity levels in a network, triad distribution.

            Background Reading:

Johnsen, E. C. 1985. "Network Macrostructure Models for the Davis-Leinhardt Set of Empirical Sociomatrices." Social Networks  7:203-24.

———. 1986. "Structure and Process: Agreement Models for Friendship Formation." Social Networks 8:257-306.

Faust, K. () “Triadic configurations in limited choice sociometric networks: Empirical and theoretical resultsSocial Networks p273-282

Bruce Kogut. (2008) Introduction to complexity: emergence, graphs, and management studies. European Management Review 4:2, 67-72

 

Class 11. Building nets from local action 2: Hierarchy

Summary: Consistent local action can have dramatic global effects.  Today we continue our discussion of local balance, focusing on the development of hierarchy and the dynamics of social groups.

Reading:

John Martin Social Structures (Cont’d)

Chase, Ivan. “Social process and hierarchy formation in small groups: A comparative perspective.American Sociological Review

Krackhardt, D. 1994. "Graph Theoretical Dimensions of Informal Organizations." Computational Organizational Theory, Editor Kathleen Carley and MichaelPrietula. Hillsdale, N.J: Lawrence Erlbaum Associates.

            Assignments: Calculate hierarchy measures for a network.

            Background Reading:

Doreian, P., R. Kapuscinski, D. Krackhardt, and J. Szczypula. 1996. "A Brief History of Balance Through Time." Journal of Mathematical Sociology 21(1-2):113-31.

Han, Shin-Kap. 2003. “Tribal Regimes in Academia: A Comparative Analysis of Market Structure Across Disciplines,” Social Networks 25:251-280

Martin, J.L. 2005 “Is Power Sexy?” American Journal of Sociology. 111:408-446

Fowler, J.H. & Jeon S. (2008) “The authority of Supreme Court precedentSocial Networks P16-30

 

Class 12. Connectivity I. Small Worlds & Complexity

Summary: Much of the power of networks comes from the inter-connection of local networks into wider populations.  Based on what we know of local networks and people’s involvement in activities, what should networks look like at the global level?

Reading: 

Kadushin, C. Chapter 7

Travers, J. and S. Milgram. “An experimental study of the small world Problem  Sociometry 32:425-443

Watts, Duncan J. (1999) “Networks, Dynamics, and the Small-World Phenomenon

   American Journal of Sociology. v. 105:493-527.

Uzzi, Brian and Jarrett Spiro. 2005. “Collaboration and Creativity: The Small World Problem.” American Journal of Sociology 111:2, 447-504

            Assignments:  Small-world connectivity test.  How many people do you know?

       Identifying components, reachability, distance.  Calculating biased network statistics.

            Background Reading:

Bruce Kogut. (2008) Introduction to complexity: emergence, graphs, and management studies. European Management Review 4:2, 67-72

Fararo, T. J. 1981. "Biased Networks and Social Structure Theorems." Social Networks 3:137-59.

Fararo, T. J. and J. Skvoretz. 1987. "Unification Research Programs: Integrating Two Structural Theories." American Journal of Sociology 92:1183-209.

Newmann, M. E. J. 1999.  “Models of the Small World”

Pool, I. d. S. and M. Kochen. 1978. "Contacts and Influence." Social Networks 1:5-51.

Rapoport, A. and W. J. Horvath. 1961. "A Study of a Large Sociogram." Behavioral Science 6:279-91.

Schnettler, S. 2009. “A structured overview of 50 years of small-world research” Social Networks

Watts, Duncan J.  1999.  Small Worlds: The Dynamics of Networks between Order and Randomness. Princeton University Press

 

Class 13.  Connectivity II: Social cohesion in diffuse settings

Summary: The power of networks to draw communities together rests on the redundancy of social relations.  Today we dig deeper into the sources of connectivity and cohesion.

Reading:

Moody, James & Douglas R. White. 2003. "Structural Cohesion and Embeddedness" American Sociological Review 68:103-127

Bearman, Farris, & Moody, "Blocking the Future" Social Science History 23:501-533

Powell, WW, DR White, KW Koput, and JO Smith. 2006. “Network Dynamics and Field Evolution: The Growth of Interorganizational Collaboration in the Life SciencesAmerican Journal of Sociology 110: 1132–205

Assignments: Identify cohesion in particular networks, plot components and bi-components from test networks. Describe how cohesion would operate in the substantive area you are working in.

Background Reading:

Klovdahl, A. S. 1985. "Social Networks and the Spread of Infectious Diseases: The AIDS Example." Social Science Medicine 21:1203-16.

Mizruchi, M. S. et al () “The Conditional Nature of Embeddedness: A Study of Borrowing by Large U.S. Firms, 1973–1994” (ASR)

 

Class 14.  Sub-Groups 1

Summary: Primary groups are common in social interaction.  How important are these groups and how do we identify them?  We will go over multiple methods for identifying a primary group.

Reading: 

Freeman, L. C. 1992. "The Sociological Concept of "Group": An Empirical Test of Two Models." American Journal of Sociology 98:152-66. (OnLine)

Frank, K. A. and J. Y. Yasumoto. 1998. "Linking Action to Social Structure Within a System: Social Capital Within and Between Subgroups." American Journal of Sociology 104:642-86. (OnLine)

Newman, MEJ. 2006. “Modularity and Community Structure in Networks” PNAS

Porter, Onnela & Mucha 2009. “Communities in Networks

            Assignments: Identify cohesive groups in test data.

            Background Reading:

Alba, R. D. 1973. "A Graph-Theoretic Definition of a Sociometric Clique." Journal of Mathematical Sociology 3:113-26.

Burt, R. S. 1987. "Social Contagion and Innovation: Cohesion Versus Structural Equivalence." American Journal of Sociology 92:1287-335.

Fershtman, M. 1997. "Cohesive Group Detection in a Social Network by the Segregation Matrix Index." Social Networks 19:193-207.

Frank, K. A. 1995. "Identifying Cohesive Subgroups." Social Networks 17:27-56.

Frank, K. A. 1996. "Mapping Interactions Within and Between Cohesive Subgroups." Social Networks 18:93-119.

Freeman, L. C. 1972. "Segregation in Social Networks." Sociological Methods and Research 6:411-30.

Friedkin, N. E. 1984. "Structural Cohesion and Equivalence Explanations of Social Homogeneity." Sociological Methods and Research 12:235-61.

Mann, CF et al. “The use of sparsest cuts to reveal the hierarchical community structure of social networksSocial Networks p223-234

Mizruchi, M. S. 1992. The Structure of Corporate Political Action. Cambridge, MA and London, England: Harvard University Press.

Mizruchi, M. S. 1993. "Cohesion, Equivalence and Similarity of Behavior: a Theoretical and Empirical Assessment." Social Networks 15:275-307.

Moody, James. 2002.  "Peer Influence Groups: Identifying dense clusters in large networks. Social Networks. 2001; 23:261-283."

T. S. Evans, R. Lambiotte. (2009) Line graphs, link partitions, and overlapping communities. Physical Review E 80:

Vaisey, Stephen (2008) “Structure, Culture, and Community: The Search for belonging in 50 Urban Communes” American Sociological Review

 

Class 15.  Sub-groups II.

Summary: (Continuation of last session, focusing on the source/creation rather than the

                                  Effects & identification)

Reading:

Baker, Wayne.  Social Structure of a Security Exchange Market. American Journal of Sociology

Feld, S. L. 1981. "The Focused Organization of Social Ties." American Journal of Sociology 86:1015-35.

            Assignments:  None

            Background Reading:

Baker, W. E. and R. R. Faulkner. 1993. "The Social Organization of Conspiracy: Illegal Networks in the Heavy Electrical Equipment Industry." American Sociological Review 58:837-60.

Feld. 1991. "Why Your Friends Have More Friends Than You Do." American Journal of Sociology 96:1464-77.

 

Class 16. Roles and Positions

Summary: Cohesive subgroups are only the most obvious structural form that results from interconnected relations.  The pattern of ties across relations can be used to induce social roles based on structural equivalence.  Here we also examine multiple relations systems. 

Reading:

Wasserman & Faust Ch 9

Nadel, A Theory of Social Structure Chapter 4.

White, H. C., S. A. Boorman, and R. L. Breiger. 1976. "Social Structure From Multiple Networks I." American Journal of Sociology 81:730-780.     

Assignments: Blockmodeling

Background Reading:

Burt, R. S. 1978. "Cohesion Versus Structural Equivalence As a Basis for Network Sub-Groups." Sociological Methods and Research 7:189-212.

Burt, R. S.1990. "Detecting Role Equivalence." Social Networks 12:83-97.

Lorrain, F. and H. C. White. 1971. "Structural Equivalence of Individuals in Social Networks." Journal of Mathematical Sociology 1:49-80.

Mandel, M. 1983. "Local Roles and Social Networks." American Sociological Review 48:376-86.

Mizruchi, M. S. 1993. "Cohesion, Equivalence and Similarity of Behavior: a Theoretical and Empirical Assessment." Social Networks 15:275-307.

 

Class 17.  Roles & Positions II.

Summary: Continuation of roles and positions, focus on technique and practical problems of block modeling.

            Reading: 

W&F Chapter 10.  Blockmodeling

Borgaiit, S. (1999) “Models of Core-Periphery Structure” Social Networks 21:375-395

Substantive papers (read at least one):

Hillman, H. (2007) “Mediation in Multiple Networks: Elite Mobilization before the English Civil War” American Sociological Review

Montgomery, JD. () “The structure of norms and relations in patronage systemsSocial Networks p565-584

            Assignments: Blockmodel assignment

            Background Reading:

Smith, D. A. and D. R. White. 1992. "Structure and Dynamics of the Global Economy: Network Analysis of International Trade 1965-1980." Social Forces 70:857-93.

Borgatti, S. P. 1999. "Models of Core / Periphery Structures." Social Networks 21:375-95.

Brieger, Ronald L. 1976. Career Attributes and Network Structure: A Blockmodel Study of a Biomedical Research Specialty American Sociological Review, Vol. 41: 117-135.

Burt, R. S. 1987. "Social Contagion and Innovation: Cohesion Versus Structural Equivalence." American Journal of Sociology 92:1287-335.

———. 1990. "Detecting Role Equivalence." Social Networks 12:83-97.

Friedkin, N. E. 1984. "Structural Cohesion and Equivalence Explanations of Social Homogeneity." Sociological Methods and Research 12:235-61.

Lorrain, F. and H. C. White. 1971. "Structural Equivalence of Individuals in Social Networks." Journal of Mathematical Sociology 1:49-80.

Padgett, J. F. and C. K. Ansell. 1993. "Robust Action and the Rise of the Medici, 1400-1434." American Journal of Sociology 98:1259-319. (its long, skim for content and method)

Rossem, R. V. 1996. "The World System Paradigm As General Theory of Development: A Cross-National Test." American Sociological Review 61:508-27.

White, D. R. and K. P. Reitz. 1989. "Re-Thinking the Role Concept: Homomorphisms on Social Networks." Pp. 429-88 in Research Methods in Social Network Analysis, Editors L. C. Freeman, D. R. White, and A. K. Romnet. Fairfax, VA: George Mason University Press.

Doreian, P. () “A multiple indicator approach to blockmodeling signed networksSocial Networks p247-258

Carroll, C. () “Canonical correlation analysis: Assessing links between multiplex networksSocial Networks p310-330

Salome, A et al () “Core/periphery structure models: An alternative methodological proposalSocial Networks p442-448

 

Class 18.  Peer Influence, Contagion & Diffusion

Summary: Networks are conduits for the flow of information and influence.  Thus, the behavior of individuals is often a complex interaction of individual and interpersonal effects.  This is a large and growing section of the field, particularly relevant in political/opinion and health research.

      Reading:

Friedkin, N. E. and K. S. Cook. 1990. "Peer Group Influence." Sociological Methods and Research 19(1):122-43. [shorter summary of argument in his book]

N. A. Christakis and J. H. Fowler (2007) “The Spread of Obesity in a Large NetworkNew England Journal of Medicine 357:370-379

Baldassarri and Bearman (2007) “Dynamics of Political PolarizationAmerican Sociological Review

Cohen, J. M. 1983. "Peer Influence on College Aspirations." American Sociological Review 48:728-34. (optional)

Assignments: Calculate peer influence measures for example data.

      Background Reading:

Centola and Macy. (2007) Complex Contagions and the Weakness of Long Ties. American Journal of Sociology 113:3, 702-734

Friedkin, N.E. 1998 A Structural Theory of Social Influence Cambridge

Haynie, Dana. Delinquent peers Revisited: Does Network Structure Matter? American Journal of Sociology. 2001; 106:1013-1057.

Kandel, D. B. "On Processes of Peer Influences in Adolescent Drug Use." Alcohol and Substance Abuse in Adolescence, Editor B. Stimmel. New York: Haworth Press.

Mikolajczyk, RT & Mirjam Kretzschmar () “Collecting social contact data in the context of disease transmission: Prospective and retrospective study designsSocial Networks p127-135

Paez et al () “Weight matrices for social influence analysis: An investigation of measurement errors and their effect on model identification and estimation quality” Social Networks p309-317

 

Class 19.  Social Exchange

Summary: Networks provide constraints and opportunities for actors.  In an exchange setting, this structure will lead to differences in power.  We contrast direct exchange and generalized exchange.

Reading:

Martin, Chapter 3

Cook, K. S., R. M. Emerson, M. R. Gillmore, and T. Yamagishi. 1983. "The Distribution of Power in Exchange Networks: Theory and Experimental Evidence." American Journal of Sociology :275-305.

Lawler, E. J. and J. Yoon. 1993. "Power and the Emergence of Commitment Behavior in Negotiated Exchange." American Sociological Review 58:465-81.

Bearman, P. 1997. "Generalized Exchange." American Journal of Sociology 102(5):1383-415.

            Assignments: Identify power status of a set of example networks.

            Background Reading:

Barrera, D () “The impact of negotiated exchange on trust and trustworthiness” Social Networks p508-526

Blau, Peter s.  Exchange and power in Social Life

Doğan, Gönül () “The stability of exchange networksSocial Networks p118-125,

Lalwer, E. J. () “Social Exchange and Micro Social Order” American Sociological Review

Molm, LD et al (*) “Building Solidarity through Generalized Exchange: A Theory of Reciprocity” American Journal of Sociology

Schaefer, D.R. () “Resource Variation and the Development of Cohesion in Exchange Networks” American Sociological Review

Van Assen and van de Rijt () “Dynamic exchange networksSocial Networks p.266-278

Vande Rijt, A & Assen () “Theories of network exchange: Anomalies, desirable properties, and critical networks” Social Networks p259-271

Willer, D. 1999. Network Exchange Theory. Westport, Connecticut: Praeger.

Willer, R. () “Groups Reward Individual Sacrifice: The Status Solution to the Collective Action Problem” Robb Willer American Sociological Review

Ziegler, R. () “What makes the Kula go round?: A simulation model of the spontaneous emergence of a ceremonial exchange systemSocial Networks p107-126

 

Class 20.  Statistical Models of Social Networks        

 

Summary: Recent statistical developments have made it possible to model networks statistically, allowing us to incorporate uncertainty from measurement and sampling.  In this session we discuss the frame for statistical modeling networks and identify the ERGM method for doing so.

            Reading:

Robins, G. et al () “An introduction to exponential random graph (p*) models for social networksSocial Networks p173-191 (Part of a special issue)

STATNET Tutorial (online) & J. of Statistical Software review issue (links here).

Morris, Martina et al (2009) “Concurrent Partnerships and HIV Prevalence disparities by race: Linking science and public health.”  American Journal of Public Health. 99:1023-1031.

            Assignments: Calculate ERGM on an example graph.

            Background Reading:

 This is a quickly growing field with roots in random graph theory.  Good background can be had by reading Baysian modeling books and statistical graph theory work.  Some current/classics relevant to sociology here:

Anderson, C., Wasserman, S., and Crouch, B. (1999).  A p* primer:  Logit models for social networks.  Social Networks. 21,37-66 (online)

Duijn, GIle & Handcock () “A framework for the comparison of maximum pseudo-likelihood and maximum likelihood estimation of exponential family random graph models” Social Networks p52-62

Krivitsky, Handcock, Raftery & Hoff (2009) “Representing degree distributions, clustering, and homophily in social networks with latent cluster random effects modelsSocial Networks

Pattison, P., and Wasserman, S. 1999.  Logit models and logistic regressions for social networks:  II.  Multivariate relations.  British Journal of Mathematical and Statistical Psychology. 52, 169-193

Robins, Pattison & Wang () “Closure, connectivity and degree distributions: Exponential random graph (p*) models for directed social networksSocial Networks p105-117

Wang, Sharpe Robins & Pattison (*) “Exponential random graph (p*) models for affiliation networksSocial Networks p12-25

Wasserman, S. and P. Pattison. 1996. "Logit Modles and Logitic Regressions for Social Networks: I. An Introduction to Markov Graphs and P*." Psychometrika 61:401-25.

 

 Class 21: Dynamics 1

            Summary:  We cover two kinds of dynamics in networks: how the network structure changes and how relationship timing affects diffusion.

            Reading:

Moody, James. The Importance of Relationship Timing for Diffusion. Social Forces. 2002; 81:25-56.

Moody, James. “Static Representations of Dynamic Networks.” (manuscript).

Moody, James, Daniel A. McFarland and Skye Bender-DeMoll. 2005. "Dynamic Network Visualization: Methods for Meaning with Longitudinal Network Movies.” American Journal of Sociology 110:1206-1241

Doreian, P., R. Kapuscinski, D. Krackhardt, and J. Szczypula. 1996. "A Brief History of Balance Through Time." Journal of Mathematical Sociology 21(1-2):113-31.

Buskens, V & van de Rijt, Arnout “Dynamics of Networks if Everyone Strives for Structural Holes” American Journal of Sociology

            Assignments: Create SoNIA movie of network

            Background Reading:

Akbar Zaheer, Giuseppe Soda. (2009) Network Evolution: The Origins of Structural Holes. Administrative Science Quarterly 54:1, 1-31

Hughes et al (2009) “Power and Relation in the World Polity: The INGO Network Country Score, 1978-1998” Social Forces

Hummell, H. J. and W. Sodeur. 1990. "Evaluating Models of Change in Triadic Sociometric Structures." Pp. 281-305 in Social Networks Through Time, Eds Jeroen Weesie and Henk Flap. Utrecht, Netherlands: ISOR.

K. G. Provan, K. Huang, H. B. Milward. (2009) The Evolution of Structural Embeddedness and Organizational Social Outcomes in a Centrally Governed Health and Human Services Network. Journal of Public Administration Research and Theory

Michelle Shumate, Janet Fulk, Peter Monge. (2005) Predictors of the International HIV?AIDS INGO Network Over Time. Human Communication Research 31:4, 482-510

Morgan, D. L., M. B. Neal, and P. Carder. 1997. "The Stability of Core and Peripheral Networks Over Time." Social Networks 19(1):9-25.

Peter Monge, Marshall Scott Poole. (2009) The Evolution of Organizational Communication. Journal of Communication 58:4, 679-692

R. Cowan, N. Jonard, J.-B. Zimmermann. (2006) Evolving networks of inventors. Journal of Evolutionary Economics 16:1-2, 155-174

Suitor, J. J., B. Wellman, and D. L. Morgan. 1997. "It's About Time: How, Why and When Networks Change." Social Networks 19(1).

Weesie, J. and H. Flap. 1990. Social Networks Through Time. Utrecht, Netherlannds: ISOR.

Class 22.  Statistical Models of Networks II: Dynamic Nnetworks

Summary:  We cover SIENA models for social networks on the dynamics of selection and influence.

            Reading:

Snijders, TAB 1996 “Stochastic Actor-Oriented Models for Network Change” Journal of Mathematical Sociology 21: 149-172

Substantive SIENA paper TBA.

            Assignments: Create SoNIA movie of network

            Background Reading:

Class 23.  New Frontiers: Summary discussion of what’s new in the field.

Summary:  Student reports on new substantive work.

            Reading:

            Assignments: Create SoNIA movie of network

            Background Reading:


Theory and Society – Class Calendar

Sun

Mon

Tuesday

Wed

Thursday

Fri

Sat

Aug 25

26

27

28

29

Class 1: Introduction & History

Class 2: Foundations of SNA: Math, Models

30

31

Sept 1

2

3

4

5

NO CLASS

Class 3: Data Collection & Quality

6

7

8

9

10

11

12

Class 4: Local Networks

Class 5: Local Networks

13

14

15

16

17

18

19

Class 6: Social Capital

Class 7: Relations through Associations

20

21

22

23

24

25

26

Class 8/9: Centrality

No Class

27

28

29

30

Oct 1

2

3

Class 10: Social Balance

Class 11: Creating Hierarchy

Fall

Break

4

5

6

7

8

9

10

Fall

Break

Fall Break

FB

Class 12: Connectivity I

11

12

13

14

15

16

17

Class 13: Connectivity II

Class 14: Social Subgroups

18

19

20

21

22

23

24

Class 15: Social Subgroups

Class 16: Roles & Positions I

25

26

27

28

                                  29

30

31

Class 17: Roles & Positions II

NO CLASS

Nov 1

2

3

4

5

6

7

Class 18: Peer Influence & Diffusion

No Class

8

9

10

11

12

13

14

Class 19: Social Exchange

Class 20: Statistical Models I: Static Graphs

15

16

17

18

19

20

21

Class 21: Dynamics Properties of Nets

Class 22: Statistical Models II: Dynamics

22

23

24

25

26

27

28

Class 23: New Frontiers

Thanksgiving Holiday

T-day

T-day

29

30

Dec 1

2

3

4

5

T-day

T-day

6

7

8

9

10

11

12

Final Paper Due