Thoughts on Digital Qualitative Research – Part 2
Part 2 of the series examines the emerging tensions and questions for qualitative research in a Big Data world.

Boyd and Crawford (2012) define the shift to Big Data as a socio-technical phenomenon. The term Big Data describes the huge amount of data aggregated through interaction online and the ability to cross-reference these large data sets for new insights. Discussing the troubling concept of data, Markham (2018) and Rogers (2013) argue that datafication as ideological focus and the methodological turn towards digital research techniques quantifying social processes pose a temptation as well as a challenge for qualitative research at the same time.
The technological ability to collect data does replace the question if qualitative oriented scholars should collect such large amounts of data (Tiidenberg, 2018), from an ethical as well as from a practical point of view (Markham, 2012). Further, these large data sets do not fully represent social phenomena (Markham, 2018), but Big Data changes the way knowledge is created and research is done by changing the instruments, the focus and the process of research (boyd & Crawford, 2012). Markham (2018, p. 520) sees the turn to the quantification in data analysis, the subsumption of qualitative inquiry as an add-on for data-driven science and the pursuit of generalizability as an “ongoing risk, which the interpretative movement has long sought to combat.”
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