Liam Berriman, Lecturer in Digital Humanities/Social Science

Over the last couple of months I’ve been involved in the development of a project with colleagues at the Sussex Humanities Lab that will look at how we conduct participatory research with children and young people using digital devices. As part of the project we will explore new ways of using different computational methods to ‘hack’ digital devices in order to make participation in research more accessible to different groups of young people. One aspect of this study will look at how we might experiment with the affordances of digital devices as ‘research tools’ in order to re-configure how they are used and the kinds of data they generate.

During the last decade, digital devices have become popular research tools for participatory and ethnographic research with young people. A great deal of participatory youth research now involves researchers and/or participants taking photographs or recording sounds using readily available digital devices, such as mobile phones. Whilst these digital devices have been used to produce a lot of fascinating research on young people’s lives, they often leave open a number of unanswered methodological and ethical questions around the mediatory role of digital devices in research. Here, I want to briefly reflect on three important ways that we need to re-think the role of digital devices in participatory research with young people:

1. Digital devices as ‘black boxes’ – A key challenge of digital devices in research are the way they ‘black box’ the processes of data collection, storage and circulation. Bruno Latour has described how ‘black boxing’ occurs “whenever a piece of machinery or set of commands is too complex” and we (as users) “need to know nothing but its inputs and ouputs” (2000: 681). For the most part, our understanding of how digital devices work, and what they are capable of, is mediated by simplified visual interfaces of menus and settings. Consequently much of the computational complexity of digital devices remains hidden from view, leaving large gaps in our knowledge as to precisely what data are collected (e.g. metadata such as GPS location), how that data is being stored (e.g. local memory or cloud services), and how that data is handled and circulated (e.g. via encrypted or unencrypted channels). These gaps in our knowledge pose significant issues for what role we allow digital devices to play in capturing data that may be ethically sensitive.



2. Digital devices as commercial products – Related to the first point, digital devices are commercially manufactured products that have not been designed for use as research tools. As researchers we ‘appropriate’ these devices, drawing on existing affordances of devices (e.g. portability, camera functionality) to facilitate specific research activities. In recent years there have been a number of innovative studies that have creatively appropriated digital devices into research – stretching and subverting their affordances. Nonetheless, the potential uses of these devices for research are by-and-large limited to the parameters set by their consumer-driven design. Consequently, the possibilities for what kinds of data can be generated are often pre-determined and closed down by their design specifications.
3. Digital devices as ‘democratising’ research? – The growing ubiquity and availability of digital devices in everyday life has paved the way for growing numbers of studies that invite participants to capture data about their lives (see for example Wendy Luttrell’s Children Framing Childhoods and Wilson & Milne’s Young People Creating Belonging). In the ‘Face 2 Face’ and ‘Curating Childhood’ studies, we invited young people to record a ‘day in their life’ using either their own digital devices or ones supplied by us. A lingering question from these studies was the extent to which such activities might be seen as ‘democratising’ research and enabling participants to share their lives on their own terms. In particular, the extent to which the parameters of research participation are foreclosed by a particular digital device. In part, this requires a more honest assessment of what forms of research participation digital devices both ‘open up’ and ‘close down’, and how this might vary for different groups of young people taking part in research (e.g. with physical disabilities).

Our study currently under development will explore new ways of ‘opening up’ digital devices within participatory youth research. In order to challenge digital devices as closed data ‘black boxes’, we will seek to explore new participatory research methodologies that involve young people ‘hacking’ research tools and specifying their affordances (such as sensory inputs) for themselves.




April 23rd, 2016

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Dr Liam Berriman, Lecturer in Digital Humanities/Social Science, University of Sussex

In 2007, Savage and Burrows predicted a ‘coming crises of empirical sociology’ as mainstream sociological methods were muscled out by new commercial data analytics techniques. Reflecting on their paper nearly a decade later, they admit that the scale of disruption caused by ‘big data’ (as it is now known) was unimaginable, even at that moment in time (Burrows & Savage 2014).

Our conceptualisation of ‘data’, and the language we use to describe it, have been irreversibly changed by the arrival of big data. For a new breed of data analysts, any dataset that is less than ‘total’ or ‘complete’ has become ‘small data’. The very language of data has been transformed by a new lexicon of analytics, real-time, tracking and scraping etc. However, remaining relatively unchanged is our language for talking about the ethics of ‘big data’.

This short piece focuses on one particular aspect of big data’s methodology – ‘data scraping’ – and the ethical questions it raises for researching young people’s lives through digital data.

According to Marres and Weltevrede (2013), scraping is an ‘automated’ method of capturing online data. It involves a piece of software being programmed (e.g. given instructions) to extract data from a particular source and creating a ‘big’ dataset that would be too onerous to capture manually.

Over the last few years, ‘scraping’ has been much lauded as a means by which data capture can be ‘scaled up’ to new analytical heights, particularly in relation to one of the most popular sources for big data capture – social media. Whilst ‘scraping’ techniques have advanced, a much slower trend has been the discussion of what ethical frameworks and language we need for robustly interrogating these techniques.

As one of the largest constituent users of social media, young people are a particularly relevant group within these debates. Data scraped from social media inevitably captures the conversations, thoughts and expressions of young people’s lives, even if as an ‘inadvertent’ by-product of research.

In 2010, Michael Zimmer reported on a study that had captured the profile data of a whole cohort of American college students on Facebook. The data had been taken without permission and a failure to appropriately anonymise the data had seen the identities of the students revealed. Zimmer’s article provided a robust critique of a growing data capture trend where all data not hidden by privacy settings was seen as consensually ‘public’, and available for analysis.

The ethical lessons learnt from incidents such as these have tended to focus more on greater care for data anonymization and security, and less on issues of consent and intrusion. Again, Zimmer (2010) has been particularly vocal in refuting claims that techniques such as anonymization through aggregation are ‘enough’[1].

How do these debates connect with young people’s social media data? Television programmes such as Teens and The Secret Life of Students[2] have played a significant role in perpetuating the idea that young people are less concerned than adults about having their data made public. However, studies have repeatedly shown that young people are highly concerned about privacy online (boyd, 2014; Berriman & Thomson, 2015), and the disclosure of their digital data (Bryce & Fraser, 2014).

A little while ago, I became aware that ‘scraping’ has a colloquial meaning in some UK secondary schools. According to Urban Dictionary (think Wikipedia for slang terms and phrases), the term ‘scrape’ is used to describe:

a person intruding on something. To say that one has come out of nowhere and intruded on a conversation. 

[E.g.] ‘two people have a conversation’, ‘another person listens in’
one person out the original two people says “scrape out” to the other person.

This colloquial definition makes reference to ‘scraping’ as an unwelcome form of eavesdropping and intrusion on a private conversation. In the context of these ethical discussions, this definition seems particularly apt. It emphasises that privacy is a concern for young people, and that unsolicited ‘scraping’ of private conversations is ethically and morally contentious.

At present, there is a lack of serious ethical debate about the scraping of young people’s digital data. The presumption of public-as-consent doesn’t cut it. We need a new ethical language for talking about these issues, and young people’s voices need to be represented in these debates.



[1] Indeed, how ‘successful’ these techniques are remains debateable – see Ars Technica, 2009

[2] Two documentary series by production company Raw for Channel 4 that followed young people’s social media lives by harvesting their Tweets, texts, and Facebook updates.

February 23rd, 2016

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