A datalogical reading of online performance

Abstract

ABSTRACT This article offers a datalogical reading of online performance. In constructing the framework for this new mode of analysing online, computationally centred performance practice, it draws on discussions of data and the datalogical in Blackman [Blackman, L. 2019. Haunted Data: Affect, Transmedia, Weird Science. London: Bloomsbury Academic]; Clough et al [Clough, P. T., K. Gregory, B. Haber, and R. Scannell. 2015. “The Datalogical Turn.” In Non-representational Methodologies: Re-envisioning Research, edited by P. Vannini. London: Taylor & Francis Group] and Chun [Chun, W. 2016. Updating to Remain the Same: Habitual New Media. Cambridge, MA: The MIT Press], as well as the practices of surveillance capitalism outlined by Zuboff [The Age of Surveillance Capitalism: The Fight for the Future at the New Frontier of Power. London: Profile Books]. In conducting the analysis, attention is specifically paid to data as a ‘process of translation’ [Blackman, L. 2019. Haunted Data: Affect, Transmedia, Weird Science. London: Bloomsbury Academic], how the audience-participant as data-subject is identified and known and the ways in which data passes in and out of bodies in these works. In looping together these underlying computational happenings with the dramaturgical practices of the performances, I argue that a richer and expanded perspective of online performance practice is afforded – one which opens up the relationships between what we see, feel and experience and the other unseen, but present happenings centred in data exchange and processing within the events in question.