Colin Porlezza

Deconstructing data-driven journalism. Reflexivity between the datafied society and the datafication of news work

  • Abstract

Informations and abstract

Keywords: Algorithms; Data Journalism; Datafication; Dataism; Reflexivity.

The datafication of society is characterized by data abundance, the increasingly dominant position of algorithms that influence the lives of millions, and a secular belief in the beneficent power of quantitative data promising a new social order. Within this wider transformation process of society, the trend of datafication has been embraced, with some resistance (Lewis, Waters 2017), within the journalistic field as well, leading to new forms of data journalism. These changes in journalism offer new opportunities to analyse the datafication of society, relying on the same means - data and algorithms - that distinguish the datafied society itself. This entails a reflexivity between the instruments that characterize a datafied society, and their implementation in journalism in order to observe them. The proposed paper offers a framework to critically analyse the reciprocal relationship between journalism and the datafied society by deconstructing the notion of datafication into four specific functions of newswork: a) the observation of datafication-related issues like dataism; b) the investigation of data-surveillance; c) the generation of new data-networks by journalists; and d) unblackboxing algorithms in order to foster algorithmic accountability. Journalism is therefore not only a reflection of the broader datafication-related transformation in society, but the central means to critically showcase its problems - albeit not being immune to challenges of transparency on its own.

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