The New Science of Networks
Course info:
Honors College 431
Winter 2006
MW10:00-11:20
303 Chapman Hall
Instructor info:
Professor Val Burris
730 PLC / 346-5001
Office hours: Wednesday 12:30-2:00 p.m.
Important note:
Many of the following files are in Adobe Acrobat (pdf) format. To read these files you will need a copy of Adobe Acrobat Reader installed on your computer. To download a free copy of Adobe Acrobat Reader, please click HERE.
Course links:
Syllabus (last updated March 6, 2006)
Assignment #1 (due January 25, 2006)
Assignment #2 (due February 1, 2006). Download PADGM.hhh and PADGM.ddd; rename as PADGM.##h and PADGM.##d .
Assignment #3 (due February 13, 2006). Download POLICY.hhh and POLICY.ddd; rename as POLICY.##h and POLICY.##d . Or you can download the DL format input file policy.txt and import it yourself into Ucinet.
Assignment #4 (due February 20, 2006). You will need the DAVIS network that is installed with UCINET.
Review articles on network theory and research
Frédéric Amblard, "Simulating Social Networks: A Review of Three Books." Journal of Artificial Societies and Social Simulation (JASS) 6 (2003). A thoughtful review of the Barabási text we are using in the class along with two other recent books on networks. Reading it will help you put some of the hype about the 'new' science of networks into perspective.
Duncan J. Watts, "The 'New' Science of Networks." Annual Review of Sociology 30: 243-270 (2004). An excellent overview of some of the main ideas of the newer research on networks coming out of physics and math and how this relates to the more longstanding tradition of network analysis in sociology and other social science disciplines.
M. E. J. Newman, "Models of the Small World: A Review." Journal of Statistical Physics 101: 819-841 (2000). A good introduction to the topic of small worlds. Provides a bit more detail than the Barabási text, especially as regards the mathematical properties of small world graphs, but not overly technical.
M. E. J. Newman, "The Structure and Function of Complex Networks." Society for Industrial and Applied Mathematics (SIAM) Review 45: 167-256 (2003). Perhaps the most complete and up-to-date overview of the new research on networks, covering such topics as the small world effect, degree distributions, clustering, random graphs, network growth, preferential attachment, and network dynamics. Filled with examples and illustrations from a variety of substantive fields. Somewhat technical in places but nevertheless accessible to a general audience.
Frans N. Stokman, "Networks: Social." Pp. 10,509-10,514 in International Encyclopedia of the Social and Behavioral Sciences. Elsevier (2001). A brief, but fairly comprehensive, overview of the main concepts and concerns of social network analysis. Touches on some of the newer developments in social network analysis not covered in the Scott text.
Ronald L. Breiger, "The Analysis of Social Networks." Pp. 505-526 in Melissa Hardy and Alan Bryman, eds., Handbook of Data Analysis. Sage (2004). These excerpts from a longer review article on social networks discuss the history of social network analysis, its relationship to other qualitative and quantitative research methods, and some of the recent extensions of network analysis to the study of culture and cognition.
Charles Kadushin, "Some Basic Network Concepts and Propositions." Chapter 2 of Introduction to Social Network Theory (forthcoming). An excellent introduction to some of the key ideas in the study of social networks. Compared with other overviews of the field, Kadushin gives more attention to the underlying concepts and theories than to specific measures or techniques of analysis.
Mark Huisman and Marijte A. J. van Duijn, "Software for Social Network Analysis." Chapter 13 in Peter Carrington, John Scott, and Stanley Wasserman, eds, Models and Methods in Social Network Analysis. Cambridge (2005). A thorough review of the main software programs available for analyzing networks, including the Ucinet program used in this course. Although Ucinet is fairly comprehensive, this review may be helpful if you want to explore some of the options for the analysis or visualization of network data that go beyond what is available in Ucinet.
Online texts and edited volumes
Robert Hanneman and Mark Riddle, Introduction to Social Network Methods, University of California Riverside (2005). This online text provides a useful complement to the introductory text we are reading by John Scott. It is a bit more advanced that is necessary for the purposes of this class, but nevertheless appropriate for an undergraduate reader and highly recommended if you wish to delve into certain topics in greater depth. One of the attractive aspects of the text is that it is organized around the menu structure of the Ucinet software program.
Ronald S. Burt, Structure Reference Manual, Columbia University (1991). Structure was one of the earliest software programs for social network analysis. The program is not very user friendly, and, apart from a few distinctive methods that are unique to the program, it is no longer widely used. Nevertheless, the reference manual to the program (if you skip through all the details dealing with the command syntax) remains an excellent introduction to some of the core concepts of social network analysis.
Douglas R. White, ed., Networks and Complexity. Special issue of the journal Complexity 8 (2002). A collection of mostly brief and highly readable articles discussing the recent advances and future prospects for network analysis in a variety of substantive fields, including molecular and evolutionary biology, genetics, ecology, language and communication, entomology, neural science, history, international relations, and economics.
Ronald Breiger, Kathleen Carley, and Philippa Pattison, eds., Dynamic Social Network Modeling and Analysis. National Academies Press (2003). An eclectic collection of relatively technical papers dealing with advances and challenges in social network research methodology. Reading the introductory Workshop Summary will give you a good overview of some of the topics and questions that are now at the forefront of social network research.
Committee on Network Science for Future Army Applications, Network Science. National Academies Press (2006). Skimming this report of a workshop sponsored by the Board on Army Science and Technology (BART) will give you an idea of how network research is viewed by the military and intelligence establishments and the applications they hope to derive from such research. The committee advising the Army includes prominent academic researchers like Albert-László Barabási and Duncan Watts.
Some interesting and useful links
International Network for Social Network Analysis. INSNA is the leading organization of researchers in the field of social network analysis. Their site offers a wealth of information and links to journals, articles, researchers, software, and data sources.
See You in the Funny Papers: Cartoons and Social Networks, an article by Linton Freeman published in Connections 23 (2000), a journal of the INSNA.
Kevin Bacon Game (Oracle of Bacon), an online database operated by the Computer Science department at the University of Virginia. The game illustrates the small world phenomenon by allowing you to link actor Kevin Bacon to any other movie star through a short number of links. A link exists if any two actors played in the same movie together. The Star Links page allows you to search for the shortest paths between any other pairs of actors.
Gallery of Network Images compiled by Mark Newman, University of Michigan. This site illustrates a variety of different approaches to the visualization of networks. Below the images are links to the publications that discuss and analyze each of the networks represented.
Network Movies compiled by James Moody, Ohio State University. Many of these are discussed in the article by James Moody, Daniel McFarland, and Skye Bender-deMoll, "Dynamic Network Visualization." American Journal of Sociology 110: 1206-1241 (2005).
Visual Complexity. This website is operated by Manuel Lima, a professional in the field of industrial design, and is devoted to the advancement of methods for visualizing complex networks. Includes a gallery of more than 250 network images, many with links to the researchers or publications from which the images were taken.
FAS Research. Another interesting gallery of network images from the fields of science and business.
Who Rules? An Internet Guide to Power Structure Research. Network analysis is widely used in the field of power structure research. Much of my own research on social networks deals with structures of corporate and political power. This site provides an overview of research in this area and links to sources of data for conducting your own power structure research.
They Rule. This site provides a sophisticated graphical interface that allows you to explore and produce maps of network links among board members of large U.S. corporations. The data is not always current (it is updated every few years) and you are limited to about 500 firms. Nevertheless, an excellent research tool.
Exploring Enron. During its investigation of Enron Corporation, the Federal Energy Regulatory Commission (FERC) made public an extensive archive of Enron company email. This website, created by Jeffrey Heer at the University of California, Berkeley, reports the results of an exploratory analysis of the Enron email archive that combines methods of network visualization and applied natural language processing (ANLP).
Pacific Ecoinformatics and Computational Ecology Lab (PEaCE Lab). This website is operated by an interdisciplinary institute that promotes awareness of ecological interdependence through research on the structure, function, and dynamics of diverse networks of organisms interacting with each other and their environment. Includes a gallery of foodweb images and links to publications on ecological networks.
Santa Fe Institute. SFI is a major center for the study of networks and complexity. Browsing their site provides an overview of work-in-progress on a variety of network related topics. See especially their Network Dynamics page.