Author:
Amaturo Enrica,De Falco Ciro Clemente
Abstract
AbstractThe growing masses of digital traces generated by the datafication process make the algorithms that manage them increasingly central to contemporary society.There is widespread agreement in considering traces and algorithms as complex objects that intertwine social and material practices with their own cultural, historical, and institutional nature (Halford et al., 2010).Accordingly, given this strong intertwining between the social world and the digital world that is formed by material and technological objects, it becomes possible to consider the algorithms and traces as socio-digital objects. For this reason, this article aims to identify the features that allow us to frame them as socio-digital objects starting from concepts borrowed from the actor-network theory (Latour and Woolgar 1879). In particular, we will first discuss opacity, authority and autonomy concepts and then see how those features emerge in digital geographical traces.
Publisher
Springer International Publishing
Reference51 articles.
1. Airoldi, M., & Gambetta, D. (2018). Sul mito della neutralità algoritmica. The Lab's Quarterly, XX(4), 25–45.
2. Amaturo, E., & Aragona, B. (2019). Per un’epistemologia del digitale: note sull’uso di big data e computazione nella ricerca sociale. Quaderni di Sociologia, 81(81-LXIII), 71–90.
3. Baskiyar, S., & Meghanathan, N. (2005). A survey of contemporary real-time operating systems. Informatica, 29(2), 233–240.
4. Bhuvaneswari, A., & Valliyammai, C. (2019). Social IoT-enabled emergency event detection framework using geo-tagged microblogs and crowdsourced photographs. In A. Abraham, P. Dutta, J. K. Mandal, A. Bhattacharya, & S. Dutta (Eds.), Emerging technologies in data mining and information security (pp. 151–162). Springer.
5. Burrell, J. (2016). How the machine ‘thinks’: Understanding opacity in machine learning algorithms. Big Data & Society, 3(1). https://doi.org/10.1177/2053951715622512