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This introduction chapter provides context and background to the concept of trace in social sciences, also presenting an overview of key concepts discussed in the subsequent chapters of this volume. Information that was not meant to be informative and evidence that did not expect to possess evidential character, traces are construed as evidence only from the vantage point of the observer, inadvertently left behind by those who produced the trace in the first place (indeed, awareness might change footprints and make them fade out). Conceived as clues rather than statements, traces prove to be useful for studying current social facts and individuals who have not yet vanished. This holds to be true especially in our contemporary platform society, due to its datafication processes and the ensuing quantification of features never quantified before; digital footprints determine the selection of the most relevant content or services to offer, creating accordingly personalized feedback. Thus, individual and collective online behavior leading to traces production is shaped by digital environments’ affordances and constraints; at the same time, such socio-technically situated traces retroact over digital systems (by fueling algorithms and predictive models), thus reinforcing, or questioning, the power relations at stake. Conclusively, a brief remark is made on future research possibilities associated with the sociology of traces.

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.

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