What should sociologists do about big data?

by Ioana Cerasella Chis

This post is a follow-up to Ioana’s article in the last issue of the Oxford Left Review, ‘Big Data: A Technology of Anxiety’, which can be found here.

Big data is presented as a tool for the materialisation of Enlightenment ideals of rationality, objectivity and development, and it is fast-paced. However, as it has been used as a technology of penality, it reveals the failure of the Enlightenment to implement its idealised reason (Abbinnett 2007). In its very attempt to overcome metaphysics, a purely data-driven, neo-positivist sociology would only retort to becoming purely metaphysical – a new form of overly speculative and dogmatic scepticism, without its claims being rooted in the material experiences of society. Scholars such as Savage and Burrows declared that the relevance of sociological methods has already been marginalised due to private firms’ accessibility to large datasets, producing a crisis to ‘empirical sociology’ (2007). Their fear was prompted partly by Savage’s attendance of the ESRC Research Methods Festival in 2004; having attended the 2014 edition, I can only confirm that ‘big data’ was one of the main terms used (for the most part positively) at the conference.

Already scholars such as Tinati have suggested that sociologists should collaborate with computer scientists, unless they are willing to gain computational expertise (Housley et. al. 2014:6). However, the quantification associated with big data methods and technological devices narrows the conceptualisation of research and knowledge (boyd and Crawford 2012:665). Mixed-methods may seem a better option, but Hesse-Biber warns of their ‘thing-ness’ (i.e. reification) as a result of a movement towards guidelines for ‘best practice’ and their formalisation as ‘design’ (2014). Social researchers should engage with technology and science critically, to maintain sociology’s normative goals of doing meaningful, problem-solving research. Although this approach entails a focus on ‘the politics of methods’ (Savage and Burrows 2007:895), one ought to be careful not to fetishise methodology. Instead, researchers should seek new ways of doing cooperative research within and outside academia, to avoid both audit culture and institutional confines in producing knowledge (Chis and Cruickshank 2014). A critical and emancipatory sociology needs to avoid abstraction and base its reasoning on evidence useful for the ‘personal troubles of milieu’ (Mills 1959:8), and on making links between individual troubles and wider social issues.

How might we find a radical potential in the surveillance-induced anxieties of the big data era? (Crawford 2014). Lack of financial and legal support, barriers to learning and coming-together, and big data based sanctions within the benefits system, all exacerbate individual vulnerability and the destruction of cooperation. A political articulation of anxiety and its link to the toxic dominant ideologies and their technologies would create a context in which the commonality of all anxieties could be acknowledged. Anxiety ought to be articulated in a way that recognises the commonality of negative experiences caused by the same processes. The sense of guilt and personal failure for not coping with a destructive system can be channelled towards mobilisation and cooperation through alliances. By creating a space for sharing affects outside quantification and control, the gaze of technological surveillance and instrumental rationality can be avoided, in favour of learning how to struggle through emancipatory praxis. Theorising anxiety in relation to big data, and contesting both terms would lead to a sociology which does not fall prey to neo-empiricism (big data epistemology) or grand theory (the risk society thesis). It would be a sociology which addresses the social construction of ‘scientific facts and technological artefacts’ (Pinch and Bijker 1984).

A sociology ‘driven’ by big data ignores the social processes behind its production and use, denying truth and possibilities of making positive change. The end result is an objectivist (highly narrow, neo-positivist) presentation of the world (which Harding calls ‘weak objectivity’), that puts pressure on individuals to conform, inducing anxiety. Instead, a sociology with ‘strong objectivity’ (that is, self-reflexive and critical of abstract beliefs (Harding 1991:149)) would place the views and experiences of the traditionally marginalised as a starting point for defining problems.

Thus, as points of departure in critiquing big data and anxiety, I have gathered four brief suggestions. Firstly, it is necessary to identify big data technology and science as part of the dominant ideology of techno-capitalist societies, whose general ethos is to extract capital and create obedient/anxious/vulnerable subjects who are made to meet arbitrary expectations. Secondly, the positive contribution of social movements to the growth of knowledge (Harding 1991:64; Cox 2014) needs to be acknowledged, together with an engagement with ‘on-the-margins’ epistemologies (decolonialism/postcolonialism, feminism, queer theory, Dis/ability studies, heterodox economics etc). Thirdly, it is equally important to find ways of using the already existent technological infrastructures for new purposes, with more popular control, to aid people’s immediate needs. Fourthly, an engagement with the previous points would lead to discussing new ways of coming-together outside reified identities and structures of domination, to develop technologies for social ends, and to create dialogic social relationships.

In the film Network, a businessman envisaged ‘one vast and ecumenical holding company, for whom all men will work to serve a common profit, in which all men will hold a share of stock – all necessities provided, all anxieties tranquilized, all boredom amused’. He continued: ‘I have chosen you, Mr. Beale, to preach this evangel’ (1976). This sequence adequately illustrates the present situation in which technological innovations are presented as producing better, more ‘cost efficient’ and ‘predictive’ (asocial) knowledge. Sociologists must refuse to accept being uncritical ‘evangelists’ for top-down agendas, to instead create a context for sharing concerns and anxieties with others in an environment of solidarity, cooperation and mutual support. Mobile applications such as ‘Happify’ (Pinola 2013) will not solve the need to care for one another: rather, they are fed with our embodied anxieties, misery and insecurities, keeping us distracted from the possibilities existent, but denied to us, in the social world. Unhappiness, dissatisfaction and anxiety cannot be ‘fixed’ technologically, but they can always be mobilised for social action.

Ioana Cerasella Chis is an MA student in Social and Political Theory at the University of Birmingham and an editor of The New Birmingham Review, a progressive student journal which publishes pre-doctorate work.



Abbinnett, R. (2007) ‘Technology and the Ethics of Penality’ in The International Journal of Technology, Knowledge and Society, vol. 3, pp. 1-5.

boyd, d. and Crawford, K. (2012) ‘Critical Questions for Big Data: Provocations for a Cultural, Technological, and Scholarly Phenomenon’ in Information, Communication & Society, vol. 15, no. 5, pp. 662-79.

Chis, I., C. and Cruickshank, J. (2014) ‘The Cost of Public Intellectuals: Reflections On Raphael Sassower’s Call for Intellectuals To Influence Elites and Their Publics’ in Social Epistemology Review and Reply Collective, vol. 4, no. 1, pp. 16-26.

Cox, L. (2014) ‘Movements Making Knowledge: A New Wave of Inspiration for Sociology?’ in Sociology, vol. 48, no. 5, pp. 954-71.

Crawford, K. (2014) ‘The Anxieties of Big Data’ on The New Inquiry website, 30th May. Available at: http://thenewinquiry.com/essays/the-anxieties-of-big-data/ [Accessed 26.12.2014].

Harding, S. (1991) Whose Science? Whose Knowledge? Thinking from Women’s Lives. Milton Keynes: Open University Press.

Hesse-Biber, S. (2014) ‘The “Thing-ness” Problem of Mixed Methods Research’ on The Research Methods Festival 2014 website. Available at: [Accessed 25.11.2014].

Housley et. al. (2014) ‘Big and broad social data and the sociological imagination: A collaborative response’ in Big Data & Society, vol.1, no. 2, pp. 1-15.

Mills, C., W. (1959) The Sociological Imagination. Oxford: Oxford University Press.

Network (1976) Directed by Sidney Lumet. USA: Metro Goldwyn Mayer (MGM) and United Artists [Film].

Pinch, T., J. and Bijker, W., E. (1984) ‘The Social Construction of Facts and Artefacts: Or How the Sociology of Science and the Sociology of Technology Might Benefit Each Other’ in Social Studies of Science, vol. 14, no. 3, pp. 399-441.

Pinola, M. (2013) ‘Happify Trains You to be Happy, Using Games Backed by Science’ on LifeHacker website, 24th October. Available at: http://lifehacker.com/happify-trains-you-to-be-happier-using-science-based-g-1451531808 [Accessed 25.12.2014].

Savage, M. and Burrows, R. (2007) ‘The Coming Crisis of Empirical Sociology’ in Sociology, vol. 41, no. 5, pp. 885-99.


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