The Social Complexity of Digital Data


The Social Complexity of Digital Data

Petter Tornberg


The deluge of digital data has become a powerful force in shaping how we think about society. Its emergence has given social scientists unprecedented access to previously unimaginable data – traces of the lives, dreams, and feelings of hundreds of millions of people. This seems to be leading to a renewed naturalism in parts of the social sciences -- a reinvigoration of the notion that, given enough data, we may find a “physics of culture” that permits prediction and control of the type that characterize the natural sciences. But this naturalism differs in important ways from the one that came before it: since digital data does not hide the intricate relational complexity or mass-interactional nature of the social, it tends to chafe with the traditional Cartesian-Newtonian paradigm. The new naturalism instead sees society through the lens of the mass-interaction and relationality that digital data provides, with naturalist analogies of “avalanches and granular flows, flocks of birds and fish” (Ball 2012, p.IX): society is increasingly understood as complex.
This development begs a revisiting of the questions of the influential mid-20th century debates on naturalism: what are the possibilities of social scientific knowledge and the limits of naturalism in our new digital world? Fundamentally, society seems characterized not merely by bottom-up emergence, but by a continuous dialectic between agency and structure; between emergence and structure; between bottom-up and top-down. People shape society, and society shapes us, as we, individually and collectively, go about changing it or maintaining it. Its structures are themselves instilled with agency, as the actors are reflexively conscious of the emergent structures of which they are part. The human capacity of reflexivity, imply the formation of “causal thickets” (Wimsatt 1994) that cut through the timescale separation that lies as a foundational cornerstone assumption of many naturalist methods, what Herbert Simon (2002) called "near-decomposability" and others through the distinction between “closed” and “open” systems. This seems to have fundamental implications for the ontological nature of society, as well as for how we approach it. This presentation hence suggests that the complexity scientific approach to society is in a need of a “turn to ontology”: the formulation of an explicit metatheory for the nature of society.
A possible source of such a metatheory is suggested to be complex realism, constituted by the integration between complexity science and critical realism, which may provide a foundations for “the development of a situated, reflexive and contextually nuanced epistemology" (Kitchin 2014) to serve a system that is not only complex, but also structured, meaning- and value-laden.
The presentation furthermore illustrates this tentative metatheoretical framework through on-going work that looks empirically at the dialectic between agency and structure, through a case study on gender expression on social media. This study looks at 500,000 photographs of men and women on Instagram and Flickr using a mixed-methods approach, including image and text analysis, to study the question of how gender, as a social structure, is perpetuated in and through a dialectic between agency and structure. The theoretical lens of Erving Goffman shows social media as a platform through which we are socialized into society through a continual "learning by posting": the platforms function as a mirror that guides us in the shaping and reshaping of our identities through repeated attempts at self-representation. This study hence also illustrates how digital data emphasize not only the quantifiability and complexity of social life, but paradoxically also precisely the distinctive features that makes society ontologically distinct: the self-reflexivity and hyperreality characteristic of postmodernity.

Ball, P., 2012. Why society is a complex matter: Meeting twenty-first century

Kitchin, R., 2014. Big Data, new epistemologies and paradigm shifts. Big Data & Society, 1(1), p.2053951714528481.
Simon, H. A. (2002). Near decomposability and the speed of evolution. Industrial and corporate change, 11(3), 587-599.
Wimsatt, W. C. (1994). The ontology of complex systems: levels of organization, perspectives, and causal thickets. Canadian Journal of Philosophy, 24(sup1), 207-274.