Vectorizing distinction: The mathematical logic of online profiling through a Bourdieusian lens

This article revisits Pierre Bourdieu's seminal work La Distinction and compares it with contemporary data analysis techniques used for online user profiling. Bourdieu's topological conceptualization of social space as a multidimensional space structured by forms of capital anticipated, in many ways, today's vector-based profiling tools used by major digital platforms. Both frameworks decompose co-occurrence matrices into geometric latent spaces where proximity encodes similarity, and both aim to connect individual social positions with tastes and preferences probabilistically. We argue that this convergence represents an independent validation of Bourdieu's theoretical intuitions and briefly discuss some implications of the new technical capabilities of corporate online profiling methods