Pols 513
Topics in Political Behavior
Political Networks: Theory, Concept, & Methods
Spring 2011
W 6:00 - 8:30
Faner 3173
Name:
Title:
Email:
Office:
Phone:
Office Hours:
1
Scott D. McClurg
Associate Professor
[email protected]
3130 Faner Hall
453-3179
8:00 - 10:00 W
2:00 - 3:00 R
By appointment
Course Description
The course serve as an introduction to social network analysis (SNA) as it pertains to the
study of social and—especially—political phenomenon. SNA is a large and growing field
that stretches across such diverse disciplines as physics, computer science, anthropology, and
sociology. This class focuses principally on the assumptions, theories, concepts, and methods
that bind the field together. Although most of the reading will come from foundational
papers in other disciplines, this unifying focus provides enough background to apply it in
any substantive area.
With this as the backdrop, particular attention is given to areas in which SNA and political science overlap. Although some of the earliest examples of empirical political science were
deeply influenced by the need to pay attention to human interaction and interdependence,
only recently has the study of political networks become part and parcel of mainstream political science. One consequence of the distance between political science and SNA is that
are exciting opportunities to reconceptualize, reconsider, and re-analyze the discipline with
fresh eyes. Another consequence is that there are significant gaps in the concepts and tools
used by social network analysis that could benefit from the insight of political science, particularly in thinking about the meaning and consequences of power. Thus, a principal theme
1
of this class is to consider the ways in which new political network analyses can bridge the
gap between these two areas of interest.
You should note that this is a very demanding class, reflecting the need to introduce
SNA and its application in political science. Yet while it is worthwhile noting the length of
the syllabus upfront, you should be just as cognizant of the fact that is but a small sample
of work in the field. Towards that end, this class is only an introduction and your ability to
master the material will depend on repeated application, empirical practice, and additional
reading. I have tried to provide a number of recommended readings through out the syllabus
to facilitate further learning.
2
Course Philosophy
Network approaches assume that social phenomenon can only be understood in the context
of the relationships between people, groups, organizations, institutions, and other units that
produce the outcomes that interest social scientists. Individuals are assumed to be free
to act, but not independent of others around them; institutions are not simple products
of rules and individual choices; and, aggregate patterns are more complex than average of
their constituent parts. This stands in stark contrast to the fundamental assumptions of
most common theoretical frameworks in economics, psychology, and business, well as parts
of sociology and anthropology. And though the assumption is not beyond question—it is,
afterall, an assumption—it is key to understanding the insights of SNA. It is the uncommonness of the assumption, particularly in political science, that gives the study of political
networks its unique character.
With this in mind, the course is structured into four units. We will begin with some
background reading on the evolution of SNA and the assumption of relational interdependence. The second unit will cover different theories influence by the principals of SNA. Our
interests here will focus squarely on how the assumptions of interdependence can to lead to
innovative thinking about social and political phenomena, both in the impact of networks
on individuals and reverse, where individuals influence the shape of the network. The third
section is strongly oriented on introducing the tools of SNA. Although the goal is to cover
most of the principal methods used in SNA, I have endervoured to introduce substantive examples to help vitiate the material. Finally, we will cover the application of the theories and
tools in political science. While my choices here inevitably reflect my interests in American
politics, examples here also demonstrate the main topics of political network analysis in a
variety of contexts.
3
3.1
Course Requirements and Graded Evaluation
Class Participation
Attendance and participation are mandatory for this course. It is imperative that you
come prepared to discuss all course material each week. To aid in your preparation, I have
2
identified some of the important themes and questions for each week on the syllabus. You
would be well served to think about those issues and others before you enter class each week.
You should also come prepared to answer the following questions for each of the assigned
readings:
1. What is the main contribution of the reading to scholarly knowledge?
2. What theoretical tradition is the reading working within or in contrast to?
3. What hypotheses are offered for empirical analysis?
4. What are the data and measures used in the paper? What methodological techniques
are used to analyze the data? Are the data and methods appropriate for evaluating
the theory and hypothesis?
5. What are the main findings?
6. What are the implications of the theory and results for our understanding of political
behavior?
7. What are your criticisms of the research?
Active participation accounts for 100 points towards your final grade. These points are to be
based on my qualitative assessment of how actively you engage the material and class, the
quality of that engagement, and your ability to forceably but respectfully engage classmates.
3.2
Labs
As SNA is a different kind of approach to social science, familiar tools of statistical and
graphical analysis do not apply here. By the same right, the tools of SNA are not available
in conventional statistical packages. To facilitate your need for familiarity with SNA software,
we will decide on a time where the the entire class can meet together to work on laboratory
exercises that will allow us to become familiar with the software package Pajek. Students will
be graded on attendance and work for these five laboratory sessions, for a total of 100 points.
You will find it helpful to order the book by deNooy et al. below. Any student wishing to
opt out of the lab may do so and have these points be transferred to participation. The
laboratories will take place during the third units, on a schedule that is agreed upon by the
instructor and class.
3.3
Weekly Talking Points
You are required to submit “talking points” ten times over the course of the semester.
Each time you make a submission, you must provide questions or comments about two
of that week’s readings. Talking points should be emailed to the entire class by email
no later than 9:00 AM on the day we have class. I will use your talking points to guide
3
the seminar discussions, so they should be the most interesting questions or arguments that
you have identified based on the weeks readings. Each comment/question should be in the
form of a short paragraph, specifically refer to the reading(s) in question, and should be no
longer than 150 words. Late talking points will never be accepted. Each of your submissions
is worth 20 points (half for completion, half for quality/insight), for a total for 200 points
towards your final grade.
3.4
Research Paper
The primary requirement of this class is a research paper (15-20 pages) on a topic of the
students choice. The goal is to identify a research question in the field of political networks
and to conduct an empirical investigation aimed at answering this question. All students
are required to use empirical data in their paper (although they need not use quantitative
data), the analysis of which is influenced by network theory, concepts, or techniques. To
facilitate this part of the requirement, I will provide information on available datasets of
interest. Ideally, this paper will eventually be a conference paper and/or journal submission.
Finished papers will be presented as a poster at a graduate research symposium (tentatively
scheduled for the week of finals) along with your colleagues in other courses. The final
paper will worth 450 points and will be judged on the quality of its writing, use of social
network material, and contribution to existing scholarship. The poster will be worth 150
points that are based on professionalism, presentation, and ability to accurately convey the
paper’s central message.
3.5
Assignment Schedule
Participation
100 points Weekly
Laboratory
100 points During 3rd Unit
Talking Points
200 points Weekly
Research Paper
450 points April 13th
Poster Presentation 150 points May 9th
3.6
Grading Scale
1000 to 900
899 to 800
799 to 700
699 to 600
Below 600
A
B
C
D
F
4
4
Class Policies
4.1
Absences
You are expected to attend every lecture and discussion section. If you arrive after attendance
is taken, you will be considered absent for the day. If you must miss class for some reason,
you can receive an excused absence by contacting me in advance. I reserve the right to see
documentation for your absence or to decide what constitutes a reasonable excuse. If you
must miss class, you are responsible for finding out what you missed.
4.2
Missed Assignments
All assignments are due at the start of class on the date assigned unless the instruct indicates
otherwise. Any assignment not turned in on time will lose half a letter grade for each day it
is late. Any assignment more than 48 hours late will not be accepted. See “Problems and
Emergencies” for the only exceptions to this policy.
4.3
Incompletes
There will be no incompletes given in this class except in cases of emergency or where
university policy applies to the contrary.
4.4
Cheating and Academic Misconduct
Any student engaging in academic misconduct will receive an F in my course and be reported
to the Dean. I will also recommend your expulsion from the graduate program. I suggest
that, as a start, you use the following common sense criteria:
• Group work not approved by the instructor constitutes academic fraud.
• Representing anyone elses written work as your own is plagiarism.
• Representing anyone elses ideas as your own is academic misconduct.
• Using unauthorized resources on exams or in papers is cheating.
• Turning in work from other classes without permission is academic misconduct.
If you have any questions about what constitutes cheating or academic misconduct, you
should examine the university policy and/or ask the instructor prior to turning in any assignment.
5
4.5
Problems and Emergencies
If a problem or emergency arises that prevents you from attending an exam, turning in a
paper, or coming to class, you should contact Professor McClurg as soon as possible. The
best way to contact me is via email ([email protected]). If you do not hear back from me
within a reasonable amount of time you may call me. Students contacting me prior to
missing an assignment will receive greater leniency. Examples of excuses that do not qualify
as problems and emergencies include, but are not limited to, the following: oversleeping,
taking too much medication, being incarcerated, or having a cold. You are welcome to
clarify what I consider to be an acceptable excuse to me at any point in the semester.
4.6
Grading Policies and Standards
Graded material is returned as promptly as possible. When students receive an exam or
assignment back and are dissatisfied with their grade, they must wait at least two days before
asking for a review. To request such a review, the student must submit a single-spaced,
one paragraph note explaining why the original grade is inappropriate. All assignments
submitted for review can be graded up or down by the Professor.
4.7
Disability Policy
It is the policy of this university and professor to help disabled students succeed in the
classroom. The student is responsible for notifying the professor and university of any special
problems or needs as soon as possible. The professor and university is responsible for doing
whatever they can within university policy to accommodate that student’s needs. It is in
your best interest to notify the professor and university immediately so that arrangements
can be made as soon as possible. More information is available from Kathleen Plesko at
Disable Student Services or at the DSS homepage.
5
Reading Assignments
We will significant parts of the following books in their entirety, so you should obtain them
as soon as possible. If you have any trouble obtaining them, notify me immediately. Books
marked with an asteric (*) are recommended, but not required.
• de Nooy, Wouter, Andrej Mrvar, and Vladimir Batagelia. 2005. Exploratory Social
Network Analysis with Pajek. Cambridge, UK: Cambridge University Press.*
• Friedkin, Noah. 1998. A Structural Theories of Social Influence. Cambridge, UK:
Cambridge University Press.
• Jackson, Matt. 2008. Social and Economic Networks. Princeton, NJ: Princeton University Press.*
6
• Knoke, David and Song Yang. 2008. Social Network Analysis. Second Edition. Thousand Oaks, CA: Sage Press. (Referred to below as K&Y.)
• Martin, John Levine. 2009. Social Structures. Princeton, NJ: Princeton University
Press.
• Wasserman, Stanley and Katherine Faust. 1994. Social Network Analysis: Methods
and Applications. Cambridge, UK: Cambridge University Press. (Referred to below as
W&F.)
6
Course Schedule and Reading Assignments
6.1
Introduction to Social Networks
January 19. History of Social Network Analysis.
Although social network analysis is an interdisciplinary field today, its roots run deepest in
sociology and anthropology. This week, we will example the principal milestones in SNA.
What were the main developments that transformed the field? Were they mainly theoretical
or methodological? How has this contributed to the field?
Required Reading
• Bonacich, P. 2004. “The Invasion of the Physicists.” Social Networks. 26(3):285-88.
• Lazer, D. In press. “Networks in Political Science: Back to the Future.” PS: Politics
and Political Science.
• Scott, J.D. 2000. “Chapter 2: The Development of Social Network Analysis.” Social
Network Analysis: A Handbook. 2nd Edition. Newbury Park, CA: Sage Press.
• W&F, pp. 3-22.
Recommended Reading
• Laumann, E.O.. 2006. “A 45-year Retrospective on Doing Networks.” Connections.
27(1): 65-90.
• Freeman, L.C.. 2004. The Development of Social Network Analysis: A Study in the
Sociology of Science. Vancouver, BC, Canada: Empirical Press.
January 26. A Relational Social Science.
The discussion this week focuses on the epistimelogical foundations of social network analysis—the notion that relations between units are important for understanding the social
outcomes. What does this mean and how is different from “methodological individualism?”
What is the relevance of networks for thinking about micro and macro outcomes? What are
7
reasons for using this type of approach? What are the reasons against it? What methodological and theoretical challenges derive from a relational approach?
Required Reading
• Borgatti, S.P., A. Mehra, D.J. Brass and G. Labianca. 2009. “Network Analysis in
the Social Science.” Science. 323:892-95.
• Butts, C. 2009. “Revisiting the Foundations of Network Analysis.” Science. 325:41416.
• McClurg, S.D. and J.K. Young. In press. “A Relational Political Science.” PS: Politics
and Political Science.
• Huckfedlt, R. 2009. “Interdependence, Density Dependence, and Networks in Politics.”
American Politics Research. 37:921-50.
• Emirbayer, M. 1997. “A Manifesto for a Relational Sociology.” American Journal of
Sociology. 103(2):281-317.
• K&Y, Chapters 1-2.
Recommended Reading
• Simmel, G. 1955. “The Web of Group-Affiliations.” In Kurt H. Wolff and Reinhard
Bendix (trans.). Conflict and the Web of Group-Affiliations. New York: The Free
Press.
• Huckfeldt, R. 1990. “Structure, Indeterminacy, and Chaos: A Case for Sociological
Law.” Journal of Theoretical Politics. 2(2):413-30.
• Ward, M., K. Stovel, and A. Sacks. In Press. “Networks Analysis & Political Science.”
Annual Reviews of Political Science.
6.2
Structural Theories from a Social Network Perspective.
February 2. Structural Theory of Action.
Speaking of methological individualism, the readings this week focus on how social structures—patterns of relationships—can influence individual behavior. This approach is different than economic, psychological, and social-psychological theories in explaining the behavior
of individuals. Yet, it still focuses on explanation of individual units. What does this suggest about social network analysis? In what ways can we explain the behavior of individuals
by focusing on network structures? Is this a valuable approach to understanding political
behavior? Why or why not?
Required Reading
8
• Friedkin, N. 1998. A Structural Theory of Social Influence. Boston, MA: Cambridge
University Press. Chapters 1, 2, 3, 4, 5, 8, and 10.
Recommend Reading
• Coleman, J., E. Katz, and H. Menzel. 1957. “The Diffusion of Innovation Among
Physicians.” Sociometry. 20:253-70.
• Christakis, N.A. and J.H. Fowler. 2007. “The Spread of Obesity in a Large Social
Network over 32 Years.” The New England Journal of Medicine. 357: 370-379.
• Bearman, P. S., J. Moody., and K. Stovel. 2004. “Chains of Affection: The Structure of Adolescent Romantic and Sexual Networks.” American Journal of Sociology.
110(1):44-91.
• Jackson, M. 2010. Social and Economic Networks. Princeton, NJ: Princeton University
Press. Chapter 7.
February 8. Structural Theory of Aggregation.
Although we often think of social structures as exercising force upon individuals, its also true
that the component units influence the structure. In the readings this week, we consider
the process of aggregation and the extent to which interdependence influence structure.
This has substantive implications and raises clear questions about causality. What are the
possible aggregate patters that arise from different types of relationships? Which types
of relationships should we expect in politics? What does this imply about aggregation in
politics? Why? Why not?
Required Reading
• Martin, John Levi. 2009. Social Structures. Princeton, NJ: Princeton University Press.
Chapters 1, 2, 3, 4, 5, 7, and 9. (Skip Chapter 8.
Recommend Reading
• Ahn, T.K., R. Huckfeldt and J.B. Ryan. Forthcoming. “Communication, Influence,
And Informational Asymmetries Among Voters.” Political Psychology.
• Burt, R. 1978. “Cohesion versus Structural Equalivalence as a Basis for Network
Subgroups.” Sociological Research and Methods. 7(2):189-212.
• Burt, R. 1987. “Social Contagion and Innovation: Cohesion Versus Structural Equalivalence.” American Journal of Sociology. 92:1287-1135.
• Burt, R. 1995. Structural Holes: The Social Structure of Competition. Cambridge,
MA: Harvard University Press.
9
February 15. Formal Theories of Network Equilibrium.
In addition to the type of “process” theories we’ve examined so part, there many different
types of network processed being examined from the perspective of dynamic, agent-based,
and formal models. These are not necessarily empirical in nature, instead using formal
techniques to theorize about unobservable processes. In that vein we will read about some
general ways to model networks mathematically. What is good and bad about these approaches to thinking about networks? To what degree should we care that these models are
“emprically grounded?” Why or why not? How would you turn these into empirical models?
How should they influence your research design?
Required Reading
• Jackson, M. 2010. Social and Economic Networks. Princeton, NJ: Princeton University
Press. Chapters 1, 3, 6, and 8.
• Siegel, D.A. 2009. “Social Networks and Collective Action.” American Journal of
Political Science. 53(1):122-38.
6.3
Data & Method
February 22. Data Collection.
One theme that emerges in our readings is that SNA has different data requirements than
“normal” approaches. It also has special requirements to consider with it comes to ethics,
measurement, sampling, and external and internal validity. This set of readings is a (very)
brief introduction to some of these topics. What are the special challenges in gathering
network data? What impact to they have on how we evaluate network research? What are
the common solutions? What’s missing from the list of things we consider? How would you
approach these problems? Do they make SNA less believable? Why or why not?
Required Reading
• Bearman, P.S. and P. Parigi. 2004. “Cloning Headless Frogs and other Important
Matters: Conversation Topics and Network Structures.” Social Forces. 83(2):535-57.
• Breiger, R.L. 2005. “Introduction to Special Issue: Ethical Dilemmas in Social Networks Research.” Social Networks. 27(2):89-93.
• Kossinets, Gueorgi. 2006. “Effects of Missing Data in Social Networks.” Social Networks. 28(3): 247-268.
• K&Y, Chapter 3.
• Laumann, E.O, P.V. Marsden, and D. Prensky. 1989. “The Boundary Specification
Problem in Network Analysis.” L.C. Freeman, D.R. White, and A.K. Romney, Eds.
Research Methods in Social Network Analysis. Fairfax, VA: George Mason University
Press. PP. 6187.
10
• Marsden, P. V. 1990. “Network Data and Measurement.” Annual Review of Sociology.
16:435-463.
• W&F, Chapter 2.
Recommended Reading
• Butts, C. 2003. “Network Inference, Error and Informant (In)accuracy: A Bayesian
Approach.” Social Networks. 25:2: 103-140.
• Klofstad, C., S.D. McClurg, and M. Rolfe. 2009. “Measurement of Political Discussion
Networks: A Comparison of Two ‘Name Generator’ Procedures.” Public Opinion
Quarterly. 73(3):462-82.
• Marsden, P.V. 1987. “Core Discussion Networks of Americans.” American Sociological
Review. 52:122-31.
March 2. Conceptualizing Networks
This week examines the basic concepts of SNA methods and introduced the idea of graph
theory. We will also get an overview of the upcoming weeks and discuss how they fit together
into a single framework. This week will be very technical and will therefore be lectureoriented, so talking points this week should focus on explaining what is unclear in the
readings.
Required Reading
• K&Y, Chapter 4.
• W&F, Chapters 3 and 4.
March 9. Spring Break.
Enjoy the break (but you probably should still be working)!
March 16. Properties of Social Networks: Relationships, Centrality, and Positions.
Because SNA can be used to consider problems at both the micro and macro levels of
analysis, they have methods for measuring and exploring both local and aggregate properties.
In this session we will examine the basic local properties of networks and consider how
they can be used for thinking about about substantive problems. You should read the
methodological material first and read the applied pieces second. Issues to consider
are what makes a “relationship” between units interesting, how do we examine properties of
actors based on their relations, and why this can be relevant to substantive problems.
Required Reading
11
• Theory and Method
– Grannovetter, M. 1973. “The Strength of Weak Ties.” American Journal of
Sociology. 78:1360-80.
– W&F, Chapters 5, 9, and 13
• Application
– Burt, Ronald S. 1987. “Social Contagion and Innovation: Cohesion versus Structural Equivalence.” American Journal of Sociology. 81(4):730-781.
– Carpenter, D., K. Esterling, and D. Lazer. 2003. “The Strength of Strong Ties:
A Model of Contact-Making in Policy Networks with Evidence from U.S. Health
Politics.” Rationality and Society. 15(4):411-440.
– Fowler, James. 2006. “Connecting the Congress: A Study of Co-sponsorship
Networks.” Political Analysis. 14(4):456-487.
Recommended Reading
• Bonacich, Phillip. 1987. “Power and Centrality: A Family of Measures.” American
Journal of Sociology. 92(5):215-239.
• Borgatti, S.P. 2005. “Centrality and Network Flow.” Social Networks. 27:55-71.
• Friedkin, Noah. 1991. “Theoretical Foundations for Centrality Measures.” American
Journal of Sociology. 96(6):1478-1504.
March 23. Properties of Social Networks: Clusters, Groups, and Communities
In addition to placing individual units into the broader structure, we’re also considered about
aggregate patterns of the structure itself. Yet since most networks are relatively connected
(every node can be reached by other nodes by some path), this can be challenging. Towards
that end, we will consider different ways of summarizing grouping and clustering. What
are the strengths and advantages of the different approaches? How can they be used in
substantive analyses?
Required Reading
• Theory and Method
– Davis, J.D. 1963. “Structural Balance, Mechanical Solidarity, and Interpersonal
Relations.” American Journal of Sociology. 68:444-62.
– W&F, Chapters 6 and 7. (Skim Chapter 14.)
• Application
– Ansell,C., C. Parsons, and K. Darden. 2002. “Dual Networks in European Regional Development Policy.” Journal of Common Market Studies. 35(3):347-375.
12
– Zhang, Y., A.J. Friend, A.L. Traud, M.A. Porter, J.H. Fowler, and P.J. Mucha.
“Community Structure in Congressional Cospononship Networks.” Physica A.
387(7):1705-1712.
– Waugh, A., L. Pei, J.H. Fowler, P.J. Mucha, and M. Porter. 2009. “Party Polarization in Congress: A Social Networks Approach.” (Skim.)
Recommending Reading
• Feld, S. 1991. “Why Your Friends Have More Friends than You Do.” American Journal
of Sociology. 96:1464-77.
• Freeman, L.C. 1992. “The Sociological Concept of ‘Group’.” American Journal of
Sociology. 98:152-66.
• Moody, J. 2002. “Peer Influence Groups: Identify Dense Clusters in Large Networks.”
Social Networks. 23:261-83.
• Newman, M. 2006. “Modularity and Community Structure in Networks.” Proceedings
of the National Academy of Science. 103(23):8577-8582.
March 30. Modeling and Hypothesis Testing.
Most of the methods discussed so far are descriptive. Since network data is frequently not
based on random samples and violates the assumption of independent units, conventional
inferential statistics often do not provide a good foundation for hypothesis testing. The
readings focus on the different methods that are being used to make inferences and establish causality. Which approach seems to be the most fruitful? What are the trade offs of
these different methods? In practice, what do data need to look like in order to use these
techniques?
Required Reading
• Cranmer, S.J. and B.A. Demaris. In press. “Inferential Network Analysis with Exponential Random Graph Models.” Political Analysis. (See )
• Christakis, N.A. and J.H. Fowler. “Examining Dynamic Social Networks and Human
Behavior.” Working Paper.
• K&Y, Chapter 5
• Lazer, D., B. Rubineau, C. Chetkovich, and N. Katz. 2010. “The Coevolution of
Networks and Political Attitudes.” Political Communication. 27:248-74.
• W&F, Chapter 15
Recommended Reading
13
• Fowler, J.H., M.T. Heaney, D.W. Nickerson, J.F. Padgett, and B. Sinclair. In press.
“Causality in Political Networks.” American Politics Research.
• Moody, J., D. MacFarland, and S. Bender-DeMool. 2005. “Dynamic Network Visualization: Methods with Meaning with Longitudinal Network Movies.” American
Journal of Sociology. 110:1206-1241.
• Robins, Pattison, Kalish, and Lusher. 2007. “An Introduction to Exponential Random
Graph (p*) Models for Social Networks.” Social Networks. 29(2): 173-191.
6.4
Applied Political Networks.
April 6. Political Behavior.
Required Reading
• Baker, A., B. Ames, and L.R. Renno. 2006. “Social Context and Campaign Volatility
in New Democracies: Networks and Neighborhoods in Brazils 2002 Elections.” American Journal of Political Science. 50(2):382-399.
• Baldassarii, D. and A. Goldberg. 2010. “Socio-Cognitive Heterogeneity in American
Public Opinion.” Available at the PN Working Paper Archive at http://opensiuc.lib.siu.edu/pn/.
• Ben-Nun-Bloom, P. and Levitan, L.C. In Press. “We’re Closer Than I Thought: Heterogeneity of Social Networks, Moral Messages and Political Persuasion.” Political
Psychology.
• Djupe, P., A. Sokhey, and C. Gilbert. 2007. “Present But Not Accounted For?
Gender Differences in Resource Acquisition.” American Journal of Political Science.
51(4):906-20.
• Nickerson, D.W. 2008. “Is Voting Contagious? Evidence from Two Field Experiments.” American Political Science Review. 102:49-57l.
• Huckfeldt, R. and J. Mendez. 2008. “Moths, Flames, and Political Engagement:
Managing Disagreement within Communication Networks.” The Journal of Politics.
70:83-96.
April 13. Political Organization.
Required Reading
• Carpenter, D., K. Esterling, and D. Lazer. 2003. “The Strength of Strong Ties: A
Model of Contact-Making in Policy Networks with Evidence from U.S. Health Politics.”
Rationality and Society. 15(4): 411-440.
14
• Christenson, D. and J. Box-Steffensmeier. “The Factors of Interest Group Networks
and Success: Organization, Issues, and Resources.” Available at the PN Working
Paper Archive at http://opensiuc.lib.siu.edu/pn/.
• Grossman, M. and C.B.K. Dominguez. 2009. “Party Coalitions and Interest Group
Networks.” American Politics Research. 37:767-800.
• Heinz, J.P., E.O. Laumann, R.H. Salisbury, and R.L. Nelson. 1990. “Inner Circles or
Hollow Cores? Elite Networks in National Policy Systems.” The Journal of Politics.
52(2):356-390.
• Klandermans, B. and D. Oegema. 1987. “Potentials, Networks, Motivations, and
Potentials: Steps Toward Participation in Social Movements.” American Sociological
Review. 52:519-531.
• Koger, G., Masket, S., and H. Noel. 2009. “Partisan Webs: Information Exchange
and Party Networks.” British Journal of Political Science. 39:633-53.
April 20. Political Institutions.
Required Reading
• Cho, W.K.T. and J.H. Fowler. 2010. “Legislative Success in a Small World: Social
Network Analysis and the Dynamics of Congressional Legislation.” The Journal of
Politics. 72(1):124-35.
• Fowler, J.H., T.R. Johnson, J.F. Spriggs, S. Jeon, and P.J. Wahlbeck. 2007. “Network
Analysis and the Law: Measuring the Legal Importance of Supreme Court Precendence.” Political Analysis. 15(3):324-46.
• Montoya, Celeste. 2008. “The European Union, Capacity Building, and Transnational Networks: Combating Violence against Women through the Daphne Program.”
International Organization. 62:359-372.
• Thurner, P.W. and M. Binder. 2008. “European Union Transgovernment Networks:
The Emergence of A New Political Space Beyond the Nation-State.” European Journal
of Political Research. 48(1):80-106.
• Victor, J.N. and N. Ringe. 2009. “The Social Utility of Informal Institutions: Caucuses
as Networks in the 110th U.S. House of Representatives.” American Politics Research.
37(5):742-66.
15
April 27. Administration, Law, and Policy.
Required Reading
• Heaney, M. 2006. “Brokering Health Policy: Coalitions, Parties, and Interest Group
Influence.” Journal of Health Policy, Policy, and Law. 31(5):887-944.
• Henry, A., M. Lubell, and M. McCoy. 2010. “Belief Systems and Social Capital as
Drivers of Policy Network Structure: The Case of California Regional Planning.” The
Journal of Public Administration Research and Theory.
• John P. Heinz, Ann Southworth, and Anthony Paik. 2003. “Lawyers for conservative
causes: Clients, ideology and social distance. Law & Society Review. 37(1):550.
• Schneider, M., J. Scholz, M. Lubell, D. Mindruta, and M. Edwardsen. 2003. “Building
Consensual Institutions: Networks and the National Estuary Program.” American
Journal of Political Science. 47(1):143-158.
• Scholz, J.T., R. Berardo, and B. Kile. 2008. “Do Networks Solve Collective Action
Problems? Credibility, Search and Collaboration.” The Journal of Politics. 70(2):393406.
May 4. Conflict and Exchange.
Required Reading
• Hafner-Burton, E., M. Kahler, and A.H. Montgomery. 2009. “Network Analysis for
International Relations.” International Organization. 63(3):559-92.
• Maoz, Z. 2009. “The Effects of Strategic and Economic Interdependence in International Conflict Across Levels of Analysis.” American Journal of Political Science.
53(1):223-40.
• Franze, R. and J. Hays. 2008. “Interdependence in Comparative Politics: Substance,
Theory, Empirics, Substance.” Comparative Political Studies. 41:742-80.
• Kim, S. and E. Shin. 2003. “A Longitudinal Analysis of Globalization and Regionalism
in International Trade: A Social Network Approach.” Social Forces. 81(2):445-71.
• Ward, W., R. Siverson, and X. Cao. 2007. “Disputes, Democracies, and Dependencies: A Reexamination of the Kantian Peace.” American Journal of Political Science.
51(3):583-601.
• Pedhzur, A. and A. Perlinger. 2006. “The Changing Nature of Suicide Attacks: A
Social Network Perspective.” Social Forces. 84(4):1987-2008.
16
Figure 1: This graph shows roughly the number of assigned pages for each class week. Plan
accordingly, especially since much of this technical reading.
17