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‘Big Data is watching you. But does it understand you?’ R(w)SM guest blogger Beth Singler responds to Paolo Gerbaudo’s talk

Beth Singler is a PhD student in the Faculty of Divinity, Cambridge.  She is a social anthropologist researching New Religious Movements, particularly those that have an online origin or community.   Her thesis is on the Indigo Children, a concept from within the New Age Movement which has formed an ideologically bound community through the Internet.  She has also written on Scientology and Jediism, and their uses of social media for conflict or legitimation.

The contemporary leap of academia, industry, and government into the adoption of big data research methodologies appears to satisfy a long held positivistic daydream about the explication of the mechanisms of the social world.  It is a hope that the noisiness of the small data of individuals’ lives can coalesce into a calmer sea of quantifiable data from which conclusions, policy, or even money, can be made. 

Paolo Gerbaudo’s March 5th talk for the Researching (with) Social Media Reading Group challenged this assumption.  He drew attention to areas in which the big data turn, in academia in particular, is flawed in its ‘detachment from the object of study.’   He highlighted the academic bias towards data collection on Twitter vis-à-vis other platforms, driven perhaps by the fact that so many academics ‘hang out’ there (… and I am @BVLSingler writing about @paologerbaudo on @DrEllaMcPherson’s website, by the way…).  Also, although it can provide relatively easy data capture, Twitter is not always the most significant site  for interactions  on a topic as this perception bias would have it, especially in the digital politics of the geographical regions that Gerbaudo’s work focuses on.  Knowing who the actors in the field are, where they are, and how they form trust relationships and recruit requires ‘participation from below,’ according to Gerbaudo.  Qualitative methods, often derided as less rigorous in this positivistic daydream, can counter such collection biases in two ways, he argued.  First, they provide contextualization that ameliorates the ‘dirty element of datasets,’ including their distortion through the collection of data around incorrect, commercially appropriated, or shared hashtags.  Second, the small data of ephemera can counter what Gerbaudo referred to as the ‘techno-libertarian network aesthetic’: networked graphical representations, in combination with the anti-leadership rhetoric of some movements, may overdetermine conclusions about leaderless structures.  

As an ethnographer, I of course agree with this repositioning of the qualitative methodologies as fundamental to big data research.  But the importance of this is not entirely unnoticed by those participating in this big data turn.  For example, the Cambridge Big Data Strategic Research Initiative has drawn together researchers from both the quantitative and the qualitative fields of the university.  Or, more infamously, leaked Powerpoint slides detailing GCHQ’s (British Intelligence) mass social media data collection program, ‘Squeaky Dolphin,’ include diagrams of a ‘Human Science Operations Cell’ made up of small data experts: ethnographers, historians, sociologists etc.  Therefore, Gerbaudo’s analysis of the big data turn as suffering from the ‘myopia of the visible’ (Melucci, 1996) – that is, knowing phenomena only through their visible effects – is perhaps itself short-sighted. There will always be uses of big data sets, as in the two above examples,  ‘invisible’ to many of us that are being driven by financial, political, and academic agendas to actualise the sea of data into useful results – and, as Gerbaudo rightly argues, that usefulness is contingent on contextualization.

About this website

This is the website for Ella McPherson's work related to her 2014-17 ESRC-funded research project, Social Media, Human Rights NGOs, and the Potential for Governmental Accountability.