Big data challenges for the social sciences: from society and opinion to replications

Author : Dominique Boullier

Big Data dealing with the social produce predictive correlations for the benefit of brands and web platforms. Beyond « society » and « opinion » for which the text lays out a genealogy, appear the « traces » that must be theorized as « replications » by the social sciences in order to reap the benefits of the uncertain status of entities’ widespread traceability.

High frequency replications as a collective phenomenon did exist before the digital networks emergence but now they leave traces that can be computed. The third generation of Social Sciences currently emerging must assume the specific nature of the world of data created by digital networks, without reducing them to the categories of the sciences of « society » or « opinion ».

Examples from recent works on Twitter and other digital corpora show how the search for structural effects or market-style trade-offs are prevalent even though insights about propagation, virality and memetics could help build a new theoretical framework.