Master's (Sc.M.) Program in Social Data Analytics

Director of Master's Program: David Lindstrom
Associate Director of Master's Program: Carrie Spearin

Social Data Analytics Handbook                                                                                                             Social Data Analytics Newsletter

Careers in the 21st century increasingly place a premium on the ability to collect, process, analyze, and interpret large-scale data on human attributes, preferences, attitudes, and behaviors and complex systems of human interactions. Such skills have concrete application and relevance to a wide variety of careers, including market research, program evaluation, policy work, advanced study in the social sciences, and financial analysis. In its latest assessment of labor market trends, the U.S. Bureau of Labor and Statistics expects the number of market research analysts to grow by 19% and data scientists by 36% during the decade of 2021-2031. These rates far outpace average growth in other professions ensuring great employment opportunities for MSDA graduates. The demand for data analysts requires professionals that are not only technically skilled, but also thoughtful about how best to use and interpret data.

The STEM-designated master’s (Sc.M.) program in Social Data Analytics in the Department of Sociology at Brown University trains students in advanced techniques for data collection and analysis. The hallmarks of the program are focused methodological training in both quantitative and qualitative methods of data collection and analysis, with cores in spatial analysis and market research, classroom instruction by active and internationally renowned researchers, and individualized supervision of applied, hands-on data analytic research on a faculty project or with an off-campus organization.

Through this program, students will develop the pragmatic and logical skills that will prepare them for a career in social research, whether basic research (such as found in academia or research institutions) or applied (such as found in policy and market research). Students will put these newly developed skills to work, as they apply the techniques they learn to the analysis of actual data from the social sciences.

The master's program is ideal for early-career students who have an existing foundation in basic statistics and social science research and who desire more focused training in order to be not only prepared, but highly competitive, in acquiring careers in market or social research or as analysts at research and policy institutions.

While this degree is based in the Sociology Department, its value extends across disciplines. Many of the master's program faculty are associates of the Population Studies and Training Center (PSTC) at Brown, an interdisciplinary social science research and graduate training center. The Spatial Analysis courses in this program are taught by experts affiliated with the Spatial Structures in the Social Sciences (S4) Initiative.

Completion Requirements
The master’s program in Social Data Analytics is a terminal degree program designed to be completed in two semesters. The program requires eight courses including an optional intensive Research Internship that is attached to a faculty Directed Research Practicum. Brown undergraduates who enter the program as fifth-year Master’s students are allowed to use up to two undergraduate courses to count towards the eight credit requirements if the courses are among the required or elective courses for the program. All entering students are required to have (1) a one-semester introductory statistics course (SOC 1100 Introductory Statistics for Social Research or an equivalent), (2) a more advanced course in statistics or a course in college calculus (MATH 0050 and 0060, or MATH 0090 or an equivalent), and (3) a one-semester course in research methods (SOC 1020 Methods of Social Research or an equivalent).

The Sc.M. degree in Social Data Analytics consists of a total of 8 courses:

Two Required courses:

  • Multivariate Statistical Methods I (SOC 2010)
  • Multivariate Statistical Methods II (SOC 2020)

Five of any of the following elective advanced analysis courses across three topical areas:

Qualitative Methods of Investigation and Market Research

  • Focus Groups for Market and Social Research (SOC 1117)
  • Context Research for Innovation (SOC 1118)
  • Market and Social Surveys (SOC 1120)
  • EPIC: Ethnographic Praxis in Industry (SOC 1127)
  • Market Research in Public and Private Sectors (SOC 1260)
  • Qualitative Methods (SOC 2210)
  • Ethnography: Theory and Practice (SOC 2250)
  • Fields and Methods of Social Research (SOC 2430) 
  • Comparative Historical Analysis (SOC 2600)

Spatial Analysis

  • Principles and Methods of Geographic Information Systems (SOC 1340)
  • Geographical Analysis of Society (SOC 1871W)
  • Spatial Thinking in Social Science (SOC 2610)
  • Geographic Information Systems and Spatial Analysis for the Social Sciences (SOC 2612)
  • Spatial Data Analysis Techniques in the Social Sciences (SOC 2960G)
  • Applications in Geographic Information Systems (SOC 2961B)

Advanced Multivariate Methods for Population Analysis and Behavioral Modeling

  • Techniques of Demographic Analysis (SOC 2230)
  • Event History Analysis (SOC 2240)
  • Statistical Methods for Hierarchical and Panel Data (SOC 2960S)
  • Causal Analysis (SOC 2960Y)
  • Computational Methods for Social Scientists (SOC 2961M)

One substantive course in Sociology

  • To be selected from a preapproved list of graduate courses (2000-level) taught in the Department of Sociology

Research Internship and Directed Research Practicum
Students may elect to enroll in a faculty Directed Research Practicum (SOC 2982) in the first or second semester in conjunction with a research internship. The internship provides students with hands-on experience in social research. Internship experiences may occur outside of the department (either off-campus with a local organization in the for-profit or not-for-profit sector or an on-campus organization) or on a faculty member's research project. Activities may range from data collection, data entry, data file management, descriptive analyses, and more advanced model estimation. Students sometimes opt to design their own project under the supervision of a faculty member.

Admission Requirements
Personal Statement: 600-1000 words in length outlining professional goals and commitment to pursuing a career in social analysis and research
GRE General: Required
GRE Subject: Not required
Transcripts: Required from all post-secondary institutions of attendance
Letters of Recommendation: Submit 3 letters of recommendation (at least one academic)
TOEFL: Required for any international applicant whose undergraduate curriculum was not taught in English
Application Deadline: February 1st

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