The lecture series on “Data Practices” explores data “in motion”, both theoretically, empirically and methodology. The proliferation of data-intensive media requires researchers to develop their conceptual vocabulary and socio-technical understanding of data production, calculation and their underlying practices and infrastructures. Throughout the lecture series, we ask how a praxeological account can enable us to account for the movement and transformation of data. We consider data practices as those practices involved in the making, calculation, storage, accounting and valuation of data among others which are socio-material and entangled with infrastructures. The lecture series is jointly organised by the DFG graduate school “Locating Media” and the DFG cooperative research centre “Media of Cooperation”.
Timo Kaerlein (Siegen) on “Social Bots and the formalization of sociality on platforms“
The growing presence of social bots on platforms like Twitter and Facebook has led to concerns among political decision-makers, specifically connected to elections and so-called fake news campaigns. Undetected bot activity has the potential to disrupt debates by distorting social web analytics, thus conveying false impressions of popularity metrics, trending issues and potentially spreading propaganda. To give an introductory overview, the talk will summarize these societal debates and discuss different approaches developed in computer science to counter-act the perceived dangers of social bots.
Seen from the perspective of media studies, social bot activities are interesting because they have to be understood as the product of a specific medial setting or environment. Social Bots point to a process of formalization of sociality underway on social media platforms that is conditioned by the political economy of data capitalism driving their development. Standardized metrics of enunciation and performance evaluation tools lead to a pre-formatting of social behavior on platforms that applies to human and non-human participants alike. The talk will trace this development back to the primal scene of human-machine communication, the Turing Test proposed in 1950, which had been developed to evaluate the performance of artificial intelligence. Whereas the Turing Test modelled intelligence as a discrete-state abstracted measure, the mass capture and replication of user behavior employed in the development of social bots similarly re-configures sociality as a formal value ready to be processed and monetized.
The aim of the talk is to understand social bots as symptoms shedding light on the politics of platforms and the data practices connecting users to the economy of data-driven capitalism.
AH - A 217/18