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Computational Social Science Concentration in the Master of Arts in Interdisciplinary Studies

Computational Social Science (CSS) is a relatively new interdisciplinary science in which social science questions are investigated with modern computational tools. Computational social scientists investigate complex social phenomenon such as economic markets, traffic control, and political systems by simulating the interactions of the many actors in such systems, on computers. They hope to gain insights which will lead to better management of the behavior of the larger social systems, i.e., prevention of market crashes, smoothed traffic flow, or maintenance of political stability. The intractability of many social problems calls for the new approaches provided by computational social science.

CSS is a highly interdisciplinary field that requires teams to plan and complete projects, be they undertaken by government, industry, or non-profit entities. Project managers of such teams, overseeing all elements of project design and execution, tend to hold PhDs. The MAIS concentration will train students to be members of these project teams, able to meaningfully contribute to background research and to project design, execution, and communication.

Prior background should include a bachelor’s degree in one of the social sciences, in computer science, in engineering, or in a relevant discipline, as well as undergraduate courses in these and related areas. Bachelor’s degrees in other areas are also eligible, but the student may be required to take additional courses in social science, mathematics, or computer science as prerequisites to admission.

This concentration will be available in fall 2011.

Concentration Requirements (Catalog Year 2010-2011)

Six core courses (18 credits)

Three required courses (9 credits): CSS 600, 605, 610

• The required CSS courses provide an understanding of the conceptual, technical, and practical foundations of computational social science.

Three elective courses (9 credits) chosen from: CSS 620, 625, 645, 692, 739

• The electives provide an understanding of the technical foundations and current work in at least two subfields of computational social science.

One research courses (3 credits) chosen from: CSS 796, 898, 899

• The research course provides students with exposure to the most current ongoing research in the field and allows them to further develop their computational research expertise.

Three-four elective courses (9-12 credits)

• The electives allow students to acquire a substantive specialization as well as additional training in social and computational science. Because of the broad spectrum of social science phenomena, methodologies, and student backgrounds, there is a large pool of potential courses. Electives may include any Mason master’s-level course in computational social science, social science, computer science, statistics, or other quantitative methods such as data visualization, information technology, and geographic information science. Electives should be selected in conjunction with and approval of the student’s advisor and the Director of CSS Graduate Studies. If the student does not have prior coursework in multivariate statistical analysis, the electives should include at least one such course relevant for the student’s chosen specialization. Students who elect to do a 5-credit project or a thesis take 9 elective credits. Students who do a 2-credit project take 12 credits.

Proposal (1 credit): MAIS 797

Project (2-5 credits) or thesis (5 credits): MAIS 798 or MAIS 799.

Total: 36

• Credits Requirements may be different for earlier catalog years. See the University Catalog archives.

Director

Claire Snyder-Hall

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Contact information

Robert Axtell

Head of the Concentration in Computational Social Science

Contact:

Karen Underwood

Academic Department Coordinator

Department of Computational Social Science

Research 1,

Room 373, MSN 6B2 Fairfax, VA 22030

703-993-9298

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Dr. Andrew Crooks

Department of Computational Social Science

Krasnow Institute for Advanced Study

George Mason University

Website: http://www.css.gmu.edu/andrew/ Blog: www.gisagents.blogspot.com