Networks Courses

2007 – 08 Courses

Group Solidarity
Michael Macy
SOC 311
Fall 2007

What is the most important group that you belong to? What makes it important? What holds the group together, and how might it fall apart? How does the group recruit new members? Select leaders? Make and enforce rules? Do some members end up doing most of the work while others get a free ride? This course explore these questions from an interdisciplinary perspective, drawing on sociobiology, economics, and social psychology, as it applies alternative theories of group solidarity to a series of case studies, such as urban gangs, spiritual communes, the civil rights movement, pro-life activists, athletic teams, work groups, and college fraternities.

The Structure of Information Networks
Jon Kleinberg
INFO 685/ CS 685
Fall 2007

Information networks such as the World Wide Web are characterized by the interplay between heterogeneous content and a complex underlying link structure. This course covers recent research on algorithms for analyzing such networks and models that abstract their basic properties. Topics include combinatorial and probabilistic techniques for link analysis, centralized and decentralized search algorithms, generative models for networks, and connections with work in the areas of social networks and citation analysis.

Networks
David Easley and Jon Kleinberg
ECON 204; INFO 204; SOC209 and CS285
Spring 2008

This interdisciplinary course examines network structures and how they matter in everyday life. The course examines how each of the computing, economic, sociological and natural worlds are connected and how the structure of these connections affects each of these worlds. Tools of graph theory and game theory are taught and then used to analyze networks. Topics covered include the web, the small world phenomenon, markets, neural networks, contagion, search and the evolution of networks.

Computational Methods for Complex Networks
Gueorgi Kossinets, WebLab Postdoctoral Associate
INFO/SOCI 485
Spring 2008

This is a survey of research methods and techniques used in the study of complex networks. Interdisciplinary in nature, the course is intended for anyone interested in computational techniques of network analysis e.g. students in Information Science, Communication, Sociology, Economics, and Bioinformatics. You may think of it as a practicum sequel for ECON204/ SOC209/ CS285/ INFO 204 and preparation for CS 685 and similar graduate courses. The course covers a range of modern methods and explores a variety of real-life datasets, from social to technological to biological networks. We will learn appropriate tools as we go (making use of the Python NetworkX toolkit).

Empirical Analysis of Industrial Organizations
Jeff Prince
AEM 694
Spring 2008

This class will develop students’ skills in determining appropriate theoretical and corresponding econometric models for applied research. It will also improve students’ proficiency with a variety of econometric models (e.g., OLS, IVs, MLE, GMM, discrete choice, etc.). Finally, the class will provide an overview of important papers in the Industrial Organization literature and cover network externalities.

Networks and Organizations 
Mary Still 
ILROB 473
Spring 2008

2006 – 07 Courses

Networks
David Easley and Jon Kleinberg
ECON 204; INFO 204; SOC 209
Spring 2007

This new interdisciplinary course examines network structures and how they matter in everyday life. The course examines how each of the computing, economic, sociological and natural worlds are connected and how the structure of these connections affects each of these worlds. Tools of graph theory and game theory are taught and then used to analyze networks. Topics covered include the web, the small world phenomenon, markets, neural networks, contagion, search and the evolution of networks.

Online Communities (Independent Study)
Michael Macy and staff
SOC 491
Spring 2007

Online communities like Flickr, Wikipedia, Facebook, LiveJournal, Second Life, and the World of Warcraft generate mountains of data that can reveal much about the nature of social interaction. Students will get hands-on experience in all phases of the research process, from literature searches to data analysis, information visualization to writing up results. This is not a reading course. Instead, students will work closely with an NSF-funded multi-disciplinary research team, gaining hands-on experience on specific research projects. 

Seminar on Communication Networks
Connie Yuan
COMM 610
Spring 2007

This seminar reviews theoretical, conceptual and analytic issues associated with social network analysis. A selection of organizational, social-psychological, and sociological theories will be discussed to examine the emergence and maintenance of network relationship, and the impact of network relationships on diverse social processes in groups, business organizations and communities. The seminar will also teach students a number of different methods to collect and analyze network data using UCINET in connection with SPSS and other statistic packages. The key objective of the seminar is to help students develop a network perspective toward social science research, and learn to integrate substantive social network theories with network analysis method to study how both the structure and the content of network relationships can influence social dynamics.

Social Networks and Social Processes (III)
David Strang
SOC 304(3040)
Fall 2006

How do groups self-segregate? What leads fashions to rise and fall? How do rumors spread? How do communities form and police themselves on the Internet? This course examines these kinds of issues through the study of fundamental social processes such as exchange, diffusion, and group formation. Focuses on models that can be explored through computer simulation and improved through observation.

Economics of Social Networks
Larry Blume
ECON 780
Spring 2006