Ph.D Program in Computational Social Sciences

The core objective of the Ph.D. program in Computational Social Science is to train graduate students to be professional computational social scientists in academia, government or business. Our program offers students a unique and innovative interdisciplinary academic environment for systematically exploring, discovering, and developing their skills to successfully follow careers in one of the areas of computational social science.

Admission Requirements and Procedures

The application deadline is February 1st. The CSS Program accepts applications for the fall semester only.

Applicants should have as background a bachelor's degree in either one of the social sciences, in computer science, engineering, or in a relevant discipline, as well as undergraduate courses in these and related areas. Bachelor's degrees in the physical or biological sciences are also eligible, but applicant may be advised to take additional courses in social science or computer science as prerequisites to admission. Minimal requirements also include one undergraduate course in calculus and knowledge of a computer programming language preferably object-based. While in the program students are expected to develop significant expertise in the utilization of computational social science resources such as agent-based simulations or other computational tools. The program maintains a simulation environment, the Multi-Agent Simulator of Neighborhoods and Networks (MASON), in collaboration with the Evolutionary Computation Laboratory (EC Lab) of the Department of Computer Science. Mathematics training beyond basic calculus is not required, but may be useful in some areas of specialization.

To apply, visit:

    For program and course content information please contact:

    Andrew Crooks, PhD
    Director of Graduate Studies
    Computational Social Science Program
    George Mason University
    4400 University Drive, MSN 6B2
    Fairfax, VA 22030 USA

    cssgrad [at] gmu [dot] edu(preferred contact)

    Degree Requirements

    The degree requires 72 credit hours, with the following functional distribution and learning objectives:

    The 18 credit hours of required CSS courses include several courses (CSS 605, 610, 645, 692) where computational projects are required. Thus, experience in developing computational models is developed early in the program.

    The 30 credit hours consisting of discipline-based social science courses, elective courses, independent research, and directed readings must be approved by the student's Advisor and the Graduate Program Director. The Graduate Director maintains a list or recommended elective courses by discipline. Elective courses may also originate from the cross-registration mechanism offered by the Consortium of Universities of the Washington Metropolitan Area (CUWMA), comprising eleven other universities in the metropolitan area of the District of Columbia, in case a specifically necessary course is required for a student's specialization. As with all non-core courses, CUWMA courses must be approved by the student's Advisor and the CSS Director of Graduate Studies.

    Up to 30 credit hours of the required 48 may be waived based on prior Master's-level training and the specific courses taken. A maximum of 24 credit hours of prior graduate coursework may be credited, provided such credits have not been used for another degree. The combined 30 credit hours of disciplinary and elective courses provide a mechanism for compensating for the diverse prior backgrounds of students (for example, computer science vs. economics). Examples: (1) a student arriving with a strong computation background (e.g., B.S. or M.S. in computer science) would use the 15 hours of electives to acquire additional social science training, in addition to the 15 hours of disciplinary social science courses; (2) conversely, a student with strong social science background (e.g., bachelor's or master's in economics) would use the 15 hours of electives to learn more about computational or computer science.

    The following professional extracurricular activities are also encouraged for advanced students: attending professional lectures and colloquia on campus and in the capital area; writing research grant proposals with faculty, with other students, or individually, especially those addressed to the National Science Foundation; writing and publishing in peer-refereed journals, including the most competitive disciplinary journals in the social sciences as well as the more specialized computational social science journals; learning the art and science of excellent teaching; presenting papers at professional conferences; attending summer training opportunities, such as those at Santa Fe Institute, ICPSR (Inter-University Consortium for Social and Political Research, University of Michigan, Carnegie Mellon University), and others. Foreign students, or American students with a writing deficiency are required to take one or more courses in ESL or in technical and scientific writing. The program director maintains a set of resources for writing and publishing in computational social science.

    The length of time required to complete the program varies, depending on a student's time commitment, resources, and academic progress in the course of study (coursework, research, exams, dissertation). Assuming a student enters the program with proper undergraduate background, has focused research motivation, and full-time enrollment, the PhD could be earned in four years, if all academic requirements are met. Some students arriving with either a Master's degree or with prior coursework in computational social science could take less than four years. Most students will require five or more years, depending on academic progress, funding, and other factors that are normally unpredictable. The next section provides an example based on a full-time "normal load." A "light load" would take longer, up to the statutory limit allowed by the University (11 years). Students with the strongest research capabilities and professional potential will ordinarily be eligible for funding through extramural grants.

    First Year Evaluation, Candidacy Examination, and Doctoral Dissertation Proposal

    During the first year every student will form a graduate studies committee, called the First Year Committee, consisting of the student's Advisor plus 2 or 3 appropriately qualified individuals. At least 3 committee members, including the Advisor, must be tenure-line faculty in the COS, CAS, ITE and/or KIAS. The purpose of this committee is twofold: (1) to assist the student in designing a specific Plan of Study for core and elective courses, based on the student's entry record and any needs to buttress social science or computational skills; and (2) to evaluate the student's progress by the end of the first year and to issue a recommendation based on such progress. A student's Plan of Study will become part of his/her file and will be reviewed periodically. A student with strong social science background upon entry will be advised to take a prevalence of computational courses as electives. Conversely, a student with strong computational background (e.g., excellent programming skills in Java or C++) will be advised to focus the elective courses on substantive social science content. The first year evaluation will be based on a comprehensive assessment of coursework, including grades, papers, and any other materials the student wishes to submit, including computational modeling projects from CSS 605, 610 or other. Based on the evaluation the First Year Committee will encourage or discourage further continuation in the program. If continuation is recommended, the student may continue towards the next goal: passing candidacy exams. The First Year Committee must be approved by the CSS Program Director.

    Assuming normal progress and continuation, during the second year every student shall form a Doctoral Dissertation Committee consisting of the student's Dissertation Advisor, who serves as Chair, plus 3 or 4 appropriately qualified individuals. The dissertation committee may simply be an enlarged First Year committee, or it may be a different committee, depending on the evolution of a student's interests. At least 3 committee members, including the Advisor, must be tenure-line faculty in the COS, CAS, ITE and/or KIAS. The Committee must be approved by the CSS Program Director. The purpose of this committee is to advise the student on preparations for the doctoral candidacy exams, and preparation, development and defense of the doctoral dissertation.

    The Candidacy Examination is taken after a student has completed all core requirements and a majority of additional course work (18 + 15 credit hours). In the "normal load" example given earlier this corresponds to roughly the fifth semester into the program, or Fall semester of the Third Year. The purpose of the Candidacy Examination is threefold: (1) to assess the student's substantive and methodological knowledge in computational social science as a whole (corresponding to the materials covered by the core courses) and in the chosen area of concentration (examples are given below); (2) to assess the students' ability to integrate materials from different courses; and (3) to assess the student's potential for a successful dissertation. Examples of areas of concentrations and potential specializations include but are not limited to the following:

    • Agent-based computational economics: trade, finance, decision-making under risk
    • Computational political economy: voting, institutions, norms, inequality
    • Computational linguistics: generative grammars, parsing, classifiers, inference
    • Social network analysis: connectivity, structure, evolution of the WWW, cyberwarfare
    • Computational anthropology: emergence of hierarchy, settlement patterns
    • Computational political science: systems of government, conflict and war, cooperation
    • Computational sociology: segregation, collective action, leadership, trust
    • Complexity theory: power laws, potential theory, criticality, bifurcation
    • Computational methodology: multi-agent systems, evolutionary computation, UML, GIS, visualization, sonification, computational epistemology

    The Candidacy Examination shall consist of written and oral parts. The written part shall contain general and specialized questions. The latter shall be specified at least in part by the student's chosen area of specialization. The written examination shall be prepared by the Program Director and the student's Advisor, who shall solicit questions from the faculty. Each question in the written examination shall be evaluated in terms of A (high pass), B (pass), or C (fail). A grade of B+ or higher is necessary for proceeding to the oral exam. The oral exam shall cover the same or related material as the written exam, for the purpose of assessing the student's ability to respond with knowledge and professionalism to questions of substance or method. The oral exam is public and may be attended by fellow students and interested faculty. Each portion of the Candidacy Examination may be retaken only once.

    Upon passing the Candidacy Examination each student shall prepare and within a year defend a Dissertation Proposal, written in the form of an extramural research grant proposal. The student shall develop the Dissertation Proposal in consultation with the Dissertation Committee. The main criteria of evaluation shall be threefold: originality, importance, and feasibility. If successfully defended, the Dissertation Committee may recommend submission to an appropriate funding agency (NSF, NIH, or other). The Dissertation Committee may also recommend different or additional coursework as necessary for improving the dissertation project, as well as specific benchmarks that the project must attain. A student becomes a Ph.D. candidate (so-called ABD status) upon passing the Candidacy Examination and successfully defending the dissertation proposal. An ABD A Ph.D. candidate student may apply for a position that accepts applicants with an expected date for degree conferral.

    Doctoral Dissertation

    The Ph.D. dissertation is the detailed written report of an original and significant research contribution to computational social science. The essence of any dissertation in computational social science - as distinct from a dissertation in traditional social science or in computational science - is given by the unique combination of (1) an original and significant substantive research question drawn from one or more of the social sciences; and (2) an approach that is fundamentally (i.e., not secondarily or accidentally) computational and/or based on a complexity-theoretic analysis that involves a computational logic. Another set of examples may be found in the articles published in peer-refereed periodicals such as the Journal of Artificial Societies and Social Simulation, many of the Working Papers of the Santa Fe Institute, or proceedings of national or international professional conferences (Agent, NAACSOS, ESSA, EUROSIS, Arrowhead) where advanced graduate students often present their dissertation research.

    Parts of the dissertation should be publishable as refereed articles or refereed conference proceedings. Previously published content may be included in the dissertation, except when the work in question was not produced in a significant way by the student. Since computational social science research is frequently collaborative in nature, it is acceptable for a student to include in the dissertation the products of such collaboration, including work produced in conjunction with the Advisor or other members of the Dissertation Committee. A collection of published papers with a common theme may constitute the dissertation. If a doubt arises, the Dissertation Committee shall determine the status of any given item.

    The dissertation defense shall take place upon recommendation of the student's Dissertation Committee, at a time and place agreeable to all, with a minimum advance notice of two weeks. The defense is open to the public and fellow students and interested faculty and staff are encouraged to attend. However, only members of the Dissertation Committee may ask questions or make comments, following a presentation by the student candidate. The Dissertation Committee recommends that the graduate faculty of George Mason University accept the student candidate for the Ph.D. degree upon a successful defense and completion of any final revisions. The Chair of the Dissertation Committee shall ensure the implementation of any final revisions, if any are requested and agreed upon by the members of the Dissertation Committee. Additionally, the Dissertation Committee may also recommend publication of the dissertation in revised form.