Corpus strategies and pragmatist complexity

Francis Chateauraynaud and Josquin Debaz (GSPR – EHESS, Paris)

Read the second part of this text Pragmatic sociology and the digital worlds: towards an alternative laboratory

Big Data presents a number of opportunities for social scientists and humanities scholars, not least of which are massive quantities of very rich social, cultural, economic, political and historical data. It also poses a number of challenges, including a skills deficit for analysing and making sense of such data, and the creation of an epistemological approach that enables post-positivist forms of computational social science. (Kitchin, 2014).

Defining the best strategies to build relevant architectures of corpus

According to Rob Kitchin, taking seriously the rise of Big Data is

coping with abundance, exhaustiveness and variety, timeliness and dynamism, messiness and uncertainty, high relationality, and the fact that much of what is generated has no specific question in mind or is a by-product of another activity. (Kitchin, 2014)

The conjunction of high-powered computation and new analytical techniques has changed the landscape. It opens a new era for social scientists able to mobilize new computer-based techniques, in order to automatically mine data, detect patterns, build predictive models or stimulate new social theories (Schroeder, 2018).

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