Across the social sciences, natural sciences, and even humanities, researchers and practitioners have increasingly come to accept the “big data” revolution, the fact that extraordinary amounts of information on every aspect of human life are now available from both public and private sources, and that increasingly powerful computers have made analyzing such data far more practical. In many respects, quantitative analysis seems the wave of the future.
At the same time, qualitative analysis will likely rise rather than diminish in importance, since we will always need to know what the data mean for the human beings who are ultimately their source. For every study analyzing hundreds of thousands of people in a Facebook friendship network, we will need qualitative data to understand what a Facebook “friend” actually means. Still, the classic difficulties between qualitative and quantitative researchers, particularly the difficulty of the latter to understand the methods and principles of the former will continue to emerge and likely become even more important to overcome.
This course is designed for qualitative researchers in academic, government, and private practice who seek to do research they can communicate not only to their peers but also to economists, statisticians, demographers, and computer scientists, particularly as these quantitative scholars adopt larger and larger data sources and, thus, come to increasingly value the benefits of large sample sizes. The course assumes basic familiarity with ethnographic or interview methods.
The first day, “Basic Principles,” identifies the main issues at play, discusses some common mistakes qualitative researchers have made when speaking to quantitative audiences, and covers basic principles researchers can adopt in their own work. The second day, “Applications,” examines particular applications, which may vary from year to year. In 2017, the focus will be social networks. We examine what qualitative research might contribute to the study of social network, and how qualitative researchers should think about, design, and write that book for an audience of quantitative network scholars.
