Supported by the National Science Foundation
Cultural domain analysis (CDA) is the study of how people in a group think about lists of things that somehow go together. These can be physical, observable things—kinds of wine, kinds of music, rock singers, foods that are appropriate for dessert, medicinal plants, ice cream flavors, animals you can keep at home, horror movies, symptoms of illness—or conceptual things like occupations, roles, emotions, things to do on vacation, things you can do to help the environment, and so on. The method comes from work in cognitive anthropology but it has since been picked up in fields such as marketing, product development, and public health. CDA involves systematic interviewing to get lists of items that comprise a coherent cognitive domain.
The data collection methods covered in this five-day course include: free lists, pile sorts, triad tests, paired comparisons and ratings. The data analysis methods include: multidimensional scaling, hierarchical clustering, property fitting (PROFIT), quadratic assignment procedure (QAP), and consensus analysis.
The methods covered in this course are based on the analysis of profile matrices and similarity matrices. The class covers the theory behind these matrices and how they can be used in many different areas of research, including the analysis of qualitative data (like text and images) and in social network analysis. Participants get hands-on practice with data collection techniques and with data analysis using Anthropac and Ucinet software.