Trust, Disconnection, Minimizing risk and Apathy

Abstract

This paper investigates how audiences are coping with digital platforms in theireveryday lives. Empirically grounded in focus groups carried out in Denmarkwith a total of 34 participants of different ages and educational backgrounds, wepresent the results of an analysis of audiences’ coping tactics in relation to trackingdata, collecting data and mining data. Based on the analysis, we find fouroverall tactics: coping by absence, coping by trust, coping by minimizing risk andcoping by apathy. We argue that these different coping tactics are employed differentlydepending on the context of the digital routines, the data collected (sensitivevs. non-sensitive data), and the dependence of the platform (private vs. public,national vs. international platforms and apps). These contextual factors are presentedin an analytical model—a coping compass—for studying individual users’coping tactics in their datafied everyday lives.

Researching publics in datafied societies: Insights from four approaches to the concept of ‘publics’ and a (hybrid) research agenda

“…However, by focusing narrowly on the workings of algorithms, however relevant this focus might be, we risk reducing the users to mere robots, and here, the long history of audience research has taught us about many forms of agency in everyday practices. Newer studies are pointing to algorithmic resistance (see, for example, Treré, 2018; Velkova and Kaun, 2019), for example, highlighting the audiences’ agency in the form of coping tactics in the datafied everyday life (Hartley and Schwartz, 2020). As pointed out by Kennedy et al (2015), questions about agency have been overshadowed by a focus on oppressive techno-commercial strategies such as data mining.…”

“…However, as Sonia Livingstone (2019) has rightly argued, audiences are represented as rather passive and inadequate in the accounts of datafication – defenceless victims of the power of media and algorithms. Thus, newer studies have begun to bring attention to the agency of users in their datafied practices by, for example, highlighting the different coping tactics employed by users or how they experience algorithms both positively and negatively as part of their everyday lives (Hartley and Schwartz, 2020; Pink et al, 2018; Ytre-Arne and Moe, 2020).…”