The Methods of Analysis Program in the Social Sciences (MAPSS) is intended to enhance the quality and vitality of empirical scientific research done by students and faculty throughout the social sciences at Stanford.
With each passing year come many new and important innovations in techniques for collecting social science data and for analyzing such data to yield insights into the human experience.
To assure that Stanford scholars keep abreast of these developments and share resources across campus to maximize our effectiveness, MAPSS will serve as an information clearinghouse and an enterprise to foster and encourage cross-disciplinary collaboration and invigoration and exchange of expertise.
MAPSS will also serve as an outreach organization to bring expertise from other academic campuses and non-academic settings throughout the US and the rest of the world to campus to enrich Stanford scholarship.
One of MAPSS's first missions has been to centralize a database of information about all of the courses on data collection and data analysis techniques that are available on campus and may serve the needs of Stanford graduate students in the social sciences.
Another MAPSS mission will be to sponsor and co-sponsor lectures on campus by Stanford faculty and by scholars from elsewhere on methods of data collection and data analysis. The colloquium series calendar is listed on this website.
James Holland Jones
Director, Methods of Analysis Program in the Social Sciences
Associate Professor of Anthropology
Fellow, Woods Institute for the Environment at Stanford University
Social Science Data and Software (SSDS) provides services and support to Stanford faculty, staff, and students in the acquisition of social science data and the selection and use of quantitative (statistical) and qualitative analysis software. SSDS staff provide these services in a variety of ways that include consulting, workshops and help documentation.
Certificate in Computational Social Sciences (CSS) provides graduate students in the social sciences with intellectual scaffolding and a curricular framework through which they can take computationally challenging classes in natural language processing, network science and data visualization. For details on the certificate and how to apply, visit the CSS certificate webpage.