"Ethno-mining": combining qualitative and quantitative data in user research
Jan Blom told me yesterday about this approach called "ethnomining", a mixed methods approach drawing on techniques from ethnography and data mining. It comes from Intel and you can get a description about it called "Ethno-Mining: Integrating Numbers and Words from the Ground Up by R. Aipperspach, T. Rattenbury, A. Woodruff, K. Anderson, J. Canny, P. Aoki. The idea is to benefit from the integration of results coming from both the processes of ethnographic and data mining techniques to interpret data, inspire design  or facilitate finding patterns in social behavior. Some excerpts I found relevant in this paper:
"in practice, either qualitative or quantitative analysis is typically used in service of the other. (...) However, ethno-mining is unique in its integration of ethnographic and data mining techniques. This integration is carried out in iterative loops between the formation of interpretations of the data and the development of processes for validating those interpretations. (...) here are two key characteristics of the iterative loops in ethno-mining. First, they can be separated into three categories based on the amount of a priori knowledge used to find and validate interpretations of the data. Second, the results of the iterative loops are frequently, although not exclusively, represented in visualizations. Visualizations have two basic affordances: they can represent both quantitative and qualitative analyses, and they exploit the visual system to support more comprehensive data analysis, particularly pattern finding and outlier detection. (...) our method seeks to expose and explicitly address the selection biases in both qualitative and quantitative research methods by checking them against one another. Ethno-mining extends its scrutiny of these biases beyond simply comparing the biases embedded in standard qualitative and quantitative techniques. It does so by tightly integrating the techniques in loops, generating mutually informed analysis techniques with complimentary sets of biases."
Why do I blog this? great article that covers methodological aspects we discussed internally. The combination of both quantitative and qualitative techniques to collect data (and make sense of it) is definitely something that we try to apply (both in Fabien's PhD research and mine). The paper here offer a relevant framework and a discussion of cases.