CP02: Mathieu O’Neil on online field theory
‘The game creates the boundary’: field/force, actor-networks, and online research
From an Actor-Network Theory (ANT) perspective, deploying an analytical framework such as ‘field theory’ amounts to adding a layer of complexity above social actors which is arbitrary and unnecessary; all that is needed, goes this argument, is to trace the associations created by the actions of the actors involved in a controversy. In contrast I aim to show why, when it comes to analysing online activist spaces, a field-theoretical approach constitutes a valuable improvement to Actor-Network Theory.
Fields are created by the constant reciprocal adjustment of elements in relation to one another: field theory initially emerged in the physical sciences through ‘various attempts to comprehend how one thing could affect another without some substantive medium’ (Levi Martin & Gregg 2013: 40). Examples include gravity, electricity and magnetism. In the social sciences, the most well-known conceptualisation came from Pierre Bourdieu, who focused on the relationships of power that constitute and shape social fields. In Bourdieu’s sociology, society is differentiated into a number of semi-autonomous, internally coherent microcosms, governed by their own ‘game rules’, yet with similar basic oppositions – between economic and cultural capital for example – and general structures. These spaces are both fields of force (power is unequally distributed) and fields of struggle (people try to maintain or modify these power relationships). A number of objections have been levelled at field theory in general and at Bourdieu’s conception in particular. They can be summarised as follows: field theory is overly deterministic; it purports to exclusively unveil social domination; and it is simply adding an unnecessary analytical level to reality. For reasons of space, this post focuses on the last of these critiques.*
The notion that field theory adds an unnecessary macro-level structure above reality is central to ANT, which is currently being used by several analysts of online networks (see for example Marres & Moats 2015, Rogers et al. 2015). It is worth quoting ANT’s most famous proponent at length: ‘Instead of trying to simulate and predict the social orders, we wish to acknowledge the limitations of the simulation approach for collective systems and prefer letting the agents produce a dynamic and collect the traces that their actions leave as they unfold so as to produce a rich data set…’ (Latour et al. 2012: 605). Yet rich data sets appear to have distinct shapes and properties, which can be described in field-theoretical terms. This point can be illustrated by referring to boundaries, actors, and connections.
If we observe a ‘game’ or ‘contest’ (sporting or otherwise) and note that team players are wearing identifiable attire, acting in concert for a common purpose, and observing similar rules of behaviour, all of which are different to that of onlookers, then we can legitimately argue that they constitute a distinct social space. They are of course connected to the family members, friends and acquaintances watching them, to other players in other games, and so on, but it is safe to say that these ties will have limited bearing on the outcome of the particular game. A similar case can be made for online spaces (though their boundaries are more fluid than that of a sporting team): participants are there for a reason, which has nothing to do with the researcher’s construction of an object, or with a web surfer’s travels: no matter from which portal one enters, or the manner in which one interacts with other online actors, the collective purpose of the participants remains their own. The game creates the boundary. Suggesting, as Latour (2005) does, that local networks can be stretched indefinitely to cover the global, macro-perspective, provided that the material traces are accounted for, appears difficult to achieve in practice. ANT’s concern not to unduly project overarching structures onto local interactions is clearly valid. However in the online context boundary-making is justified by the socio-technical affordances of the Internet: for example the use of certain hashtags effectively circumscribes online fields.
In terms of players, an oft-mentioned contribution of ANT is to incorporate non-human actors into the network of connections and translations (Latour 2005). To return to the sports field example: no doubt the quality of the pitch and ball play a significant role; granted, the game would be vastly different without the referee’s whistle or the goal posts. Yet there is a fundamental difference in terms of agency between non-human and human actors: the whistle cannot blow itself; the ball cannot score a goal of its own volition. Both are dependent on human intervention. Similarly online there is a need to distinguish between actors who can autonomously make connections (such as people and, arguably, ‘bots’) and those who, though enabling important affordances in the diffusion of activism and controversies, rely on others to connect (to) them, such as Twitter hashtags. Nor are the algorithms that orient interactions across networks ‘just another actor’: non-algorithmic actors have no choice as to how algorithms affect them, so it makes better sense to define algorithms such as Google’s PageRank as governance institutions, whose influence stretches over the whole field.
Finally, not all connections are equal. It is far easier to create connections in Web 2.0 (by retweeting or liking a post, for example) than on Web 1.0, where hyperlinks have to be written into website link pages. Connections should accordingly be interpreted differently. Assuming that connections occur smoothly and naturally also overlooks a key fact, which is that actors may choose not to connect to one another. I have previously argued that in the online environment, where creating connections is at once costless and public, the absence of ties is highly significant: specifically, my co-author and I showed how activist actors who connected to similar issue-frames were not hyperlinking to each other’s websites, and we interpreted this absence of connection as indicating that there were major divisions in this field (Ackland & O’Neil 2011). In sum, like ANT, the version of field theory defined here acknowledges the desirability of staying at ground level. This is why our central concept of ‘field/force’ refers to the highly contingent capacity of actors to attract connections. But we also contend that this capacity or skill is inscribed in a local context: force operate in specific fields.
Ackland, R. & O’Neil, M. (2011). Online collective identity: the case of the environmental movement. Social Networks, 33(3), 177-190.
Latour, B. (2005). Reassembling the social: An introduction to Actor-Network Theory. Oxford, UK: Oxford University Press.
Latour, B., Jensen, P., Venturini, T., Grauwin, S., Boullier, D. (2012). ‘The whole is always smaller than its parts’ – a digital test of Gabriel Tardes’ monads. British Journal of Sociology, 63(4), 590-615.
Levi Martin, J. & Gregg, F. (2015). Was Bourdieu a field theorist? In M. Hilgers and Eric Mangez (Eds.), Bourdieu’s theory of social fields: Concepts and applications (pp. 39- 61). Oxon, UK: Routledge.
Marres, N. and Moats, D. (2015). Mapping controversies with social media: The case for symmetry. Social Media + Society, 1, 1-17.
Rogers, R., Sánchez-Querubín, N., Kil, A. (2015). Issue mapping for an ageing Europe. Amsterdam: Amsterdam University Press.
*To find out how we characterise an online field empirically, we invite interested readers to look at O’Neil, M. & Ackland, R. (in press) Towards a theory of online field/force. In M. Allen, J. Hunsinger & L. Klastrup (Eds.), International Handbook of Internet Studies Vol.2. Amsterdam: Springer. (Accepted 8/2/2016)] from which parts of this post originate. A pre-print of the chapter can be read on SSRN [http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2769684].