An unexpected journey: A few lessons from sciences Po médialab's experience

Tommaso Venturini (1, 2) , Mathieu Jacomy (1) , Axel Meunier (1) , Bruno Latour (1)

1 médialab - médialab (Sciences Po)
2 DANTE - Dynamic Networks : Temporal and Structural Capture Approach

In this article, we present a few lessons we learnt in the establishment of the Sciences Po médialab. As an interdisciplinary laboratory associating social scientists, code developers and information designers, the médialab is not one of a kind. In the last years, several of such initiatives have been established around the world to harness the potential of digital technologies for the study of collective life. If we narrate this particular story, it is because, having lived it from the inside, we can provide an intimate account of the surprises and displacements of digital research. Founding the médialab in 2009, we knew that we were leaving the reassuring traditions of social sciences to venture in the unexplored territory of digital inscriptions. What we couldn't foresee was how much such encounter would change our research. Buying into gospel of Big Data, we imagined that the main novelty of digital research came from handling larger amounts of data. We soon realized that the interest of digital inscriptions comes instead from their proliferating diversity. Such diversity encouraged us to reshape our professional alliances, research practices and theoretical perspectives. It also led us to overcome several of the oppositions that used to characterize social sciences (qualitative/quantitative, situation/aggregation, micro/ macro, local/global) and to move in the direction of a more continuous sociology.

Mots clés: digital sociology; computational social sciences; datascape navigation; digital methods; quali-quantitative methods; Actor-network theory; digital sociology

Domaines: Sociologie; Méthodes et statistiques

Tommaso Venturini, Mathieu Jacomy, Axel Meunier, Bruno Latour. An unexpected journey: A few lessons from sciences Po médialab's experience. Big Data & Society, 2017, 4 (2), ⟨10.1177/2053951717720949⟩. ⟨hal-01670177⟩