ABSTRACT
This chapter compares the commonalities and differences between psychoanalysts and big data analysts regarding their attitudes towards data, their presuppositions regarding data analysis and their methods of satisfying the desires of data donors. The controllability or freedom from (the result of) the data analysis can be treated as another criterion of the digital divide. The chapter focuses on 'data mining' as a method for analysing big data. The report of the McKinsey Global Institute defines data mining as the following: A set of techniques to extract patterns from large datasets by combining methods from statistics and machine learning with database management. The chapter also summarises big data analysts' presuppositions as a presupposition of assuming a super-population only after building a statistical model; and as a presupposition of objectivity dependent on the possibility of updating the statistical models. Resistance is closely linked to the psychoanalytical way of viewing the causes of mental illnesses.
