LM: Medialab Katowice has been following a hybrid approach in analyzing the cultural life of the city, which relies both on traditional methods of cultural research and on analyzing large data sets gathered from Facebook and other online sources. Can you see any benefits of that approach?
KvS: Yes, such an approach is not only beneficial, but I would even go so far as to say that it is necessary. At Utrecht Data School, our data analysis is often developed jointly with an ethnographic approach. We also use a number of mixed methods where e.g. statistical text analysis is connected with close reading of texts. Another approach we follow is using the quantitative analysis of geo-data that informs qualitative research in the field that is described by such data.
LM: What would be the added value of contrasting a data set of a particular type with another one?
KvS: It should be evident by now that data don’t speak for themselves! Data-driven knowledge production is context specific and offers only particular types of knowledge. Social media users, for instance, are not representative of society. Ultimately, there are important questions about human life that quantitative data cannot answer. Therefore, in addition to using both off- and online data, like many other researchers, I would propose that there is a great benefit in toggling between so-called ‘distant reading’ and ‘close reading’.
LM: How to remain critically reflective towards both possibilities and limitations that come with working with (Big) Data sets and studying complex social and cultural phenomena through data?
KvS: If datafication is yet another process of mediatization, as we argued, a humanities scholar is particularly well suited to scrutinize this process of translation. She can’t, however, rely only on distinct skills and methods, but need to develop what has been called Digital Bildung, which is, as Rieder and Röhle explain, the ability to think with and in technology as knowledge tools.
LM: What does it mean for a (data) researcher?
KvS: At Utrecht Data School, we teach our students about many ‘interpretive acts’ that take place in the selection, collection and analysis of data and the visualization of results. This coincides with “tool criticism”, thinking about the epistemological impact of knowledge technologies, and also raising ethical concerns.