This article explores the growing role of traces and footprints in social science, giving an outline of the main concepts and empirical questions discussed in this special issue. Remarkably, the study of traces (unobtrusive, necessarily interpretative, theory-driven and data-fueled at the same time) considers them as unwillingly insightful and strategic materials. However, the difference between information “intentionally transmitted” and information “accidentally leaked” gets fuzzy especially in online communication and social network. In this sense, by interpreting the “digital data deluge” as a social trace deluge, issues of algorithmic environments, users’ participation, datafied biases, and transparency are addressed. Finally, it is argued that traces, data exhaust, and residual information help overcoming standard dichotomies in social science (e.g., human vs. non-human realms, quantitative vs. qualitative, online vs. offline activities), both methodologically and theoretically.
Brushing society against the grain. Digital footprints, scraps, non-human acts, crumbs, and other traces / Comunello, Francesca; Martire, Fabrizio; Sabetta, Lorenzo. - In: AMERICAN BEHAVIORAL SCIENTIST. - ISSN 0002-7642. - (2022).
Brushing society against the grain. Digital footprints, scraps, non-human acts, crumbs, and other traces
comunello francesca
;martire fabrizio;sabetta lorenzo
2022
Abstract
This article explores the growing role of traces and footprints in social science, giving an outline of the main concepts and empirical questions discussed in this special issue. Remarkably, the study of traces (unobtrusive, necessarily interpretative, theory-driven and data-fueled at the same time) considers them as unwillingly insightful and strategic materials. However, the difference between information “intentionally transmitted” and information “accidentally leaked” gets fuzzy especially in online communication and social network. In this sense, by interpreting the “digital data deluge” as a social trace deluge, issues of algorithmic environments, users’ participation, datafied biases, and transparency are addressed. Finally, it is argued that traces, data exhaust, and residual information help overcoming standard dichotomies in social science (e.g., human vs. non-human realms, quantitative vs. qualitative, online vs. offline activities), both methodologically and theoretically.File | Dimensione | Formato | |
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