Working with image cards in social research

As part of my experiments with innovative methods for social research and developing design sociology, I have been using a set of image cards developed by Dan Lockton and his team at the Imaginaries Lab for their New Metaphors workshops. Dan has kindly made these resources open access (see here). The cards consists of two types: 1) a range of diverse images of things, activities and experiences that exist in people’s everyday lives (natural phenomena like clouds, rain, trees or animals and things from built environments such as cracks in pavements, graffiti and the hum of a fridge); and 2) a range of topics, concepts or ideas (for example, safety, love, fame, half-remembered dreams and personal security). I printed out a set of the New Metaphors cards, and over the past two weeks have run two pop-up methods workshops at my Vitalities Lab to experiment with them.

The two groups who came along to the workshops (there were about 15 people at the first one and ten at the second workshop) participated in activities that I devised, and then provided feedback on how they found the activities and how they thought they could use the cards in their own research or teaching. The feedback from both workshop groups was very positive: members enjoyed working with these cards and thinking about how they could use them.

At the first workshop, I used a worksheet I downloaded from the Imaginaries Lab and a research activity worksheet that I had crafted myself. After the first workshop, I developed a new worksheet, and renamed the activity ‘Vital Images Method’ to better describe what I was wanting to do with it. The two worksheets I developed are provided  below. They can be downloaded at the links here as well: VITAL IMAGES METHOD – worksheet 1 VITAL IMAGES METHOD – worksheet 2

VITAL IMAGES METHOD: WORKSHEET 1

Image [title]:   _______________________________

Choose an image card. Describe what you think of, see, feel when you look at this image.

Topic [title]: ___________________________________________

Choose a topic card. Describe what you think of, see, feel when you consider this topic.

Circle words that are shared. What are the similarities and differences? What new or surprising connections do you see?

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Worksheet 1

 

VITAL IMAGES METHOD: WORKSHEET 2

 People can work as individuals, in pairs or in small groups.

Identify a topic (e.g. big data, apps, data privacy, smartphones, fitness, exercise, good health, a specific health condition, a risk or threat) that you would like your research participants to focus on.

Ask your participants to sort through the image cards and pull out some (say three or four cards) that they associate with the topic (in present day or a specified period into the future [10 years, 20 years etc]). Ask them to reflect on these questions (they can write these reflects down or record them using a voice recording device):

  1. What do these images mean to you in relation to the topic?
  2. Why do you think you chose them?
  3. What feelings/emotions do they inspire in relation to this topic?
  4. Did these images provoke new connections or ideas for you?
  5. Did you make any connections or ideas that surprised you?

Alternative approach: rather than ask participants to choose image cards, provide them with cards randomly, and ask them to undertake the same reflections.

Extensions

  1. Make a drawing or map of the connections you see between the image and the topic.
  2. Write a short story or make a story board based on the ideas generated by the images.
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Worksheet 2

 

Analysis

The participants’ reflections can be used as research data – as a way of inquiring into the often unrecognised or unacknowledged memories, feelings and associations that people draw on to give meaning to their worlds.

Schedule for trip to Copenhagen and London, June 2019

I am giving some talks in Copenhagen and London next month. Here is the schedule for those who might want to come along.

Vitalities Lab Newsletter Number 2

VITALITIES LAB NEWSLETTER

Number 2, 29 April 2019

The Vitalities Lab is led by SHARP Professor Deborah Lupton, Centre for Social Research in Health and Social Policy Research Centre, UNSW Sydney. Further details here.

New Publications

 

Presentations

 

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Deborah speaking at the CSRH seminar series

  • Deborah Lupton: ‘The internet both reassures and terrifies’: using the story completion method for health research. Presentation for the Centre for Social Research in Health Seminar Series, 2 April 2019
  • Deborah Lupton: ‘”Smart” health promotion: a perspective from digital sociology’. Invited presentation at a sub-plenary on smart health promotion, International Union for Health Promotion and Education World Conference, Rotorua, New Zealand, 10 April 2019
  • Deborah Lupton: ‘The more-than-human worlds of self-tracking for health and fitness’. Keynote at the World Congress of the Sociology of Sport, Dunedin, New Zealand, 24 April 2019
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The campus at the University of Dunedin, where Deborah gave a keynote

 

Upcoming events

  • 6 May: Deborah will be holding a  Vitalities Lab in-house pop-up methods workshop using the ‘New Metaphors’ inspiration cards
  • 7 May: Deborah is presenting a workshop on ‘Increasing your academic visibility’. Registration is free and open to all. Further details here.
  • 13 May: Deborah is the convenor and one of the panel speakers at the UNSW Grand Challenges Event ‘Shaping our digital future’. Registration is free and open to all. Further details here.

Opportunities

  • The Vitalities Lab has a doctoral research stipend worth $30,000 annually for four years for a domestic candidate who meets UNSW Sydney requirements for doctoral admission and wishes to pursue a project related to the Lab’s research directions. Contact Deborah Lupton (d.lupton@unsw.edu.au for further details).
  • Research practicums are also available for international doctoral students who are pursuing their studies at a university outside Australia to spend a period of time as a visiting researcher at the Vitalities Lab under Deborah Lupton’s supervision. Tuition fees apply. Further details are available here.

 

Ten tips for increasing your academic visibility

It is important that academic researchers draw attention to their research. We don’t engage in scholarship just for our own benefit. We want others to be aware of and use our research, including those outside the academy. Quite apart from the high value given to factors such as impact, stakeholder engagement and numbers of citations to your work, promoting goodwill and strong networks with your colleagues is important for your flourishing, including feeling part of a community and that you are making a difference.

Here are some ideas for increasing the visibility of your research to as great a range of publics as possible.

  1. Actively use social media: blog, tweet, sign up to Facebook groups of interest or make one of your own to bring like-minded researchers together. Use these networks to publicise your activities – including new publications, calls for papers, and event announcements. Be a good academic citizen and also publicise the outputs and activities of your colleagues – they will likely return the favour.
  2. Sign up to platforms such as ResearchGate and Academia.edu and maintain your profile, updating new publications on it. These platforms provide an easy way for people to request copies of your publications and for you to share them.
  3. Publish preprints and postprints in open access outlets such as your university e-repository, ResearchGate, Academia.edu, Social Science Research Network etc. This will make your work readily accessible for those who can’t access academic journals.
  4. Ensure that you have a Google Scholar profile that lists all your publications and citations. I can’t emphasise enough how important this is to make your publications and citations visible in one place. Google Scholar automatically links to all your open access publications as well, helping people to readily find your work. Important! – ensure that you check your profile regularly to weed out any inaccuracies that the Google Scholar algorithms may have created, such as not including a publication of yours or wrongly attributing someone else’s publications (and citations) to you. An inaccurate Google Scholar profile is not a good look, particularly if it appears that you are taking credit for someone else’s work.
  5. Sign up to Google Scholar alerts for your name – this will mean that every time you are cited, GS will email you a notification. This a fantastic way not only of seeing who is citing you but also how they are using and building on your work.
  6. Create some kind of web presence for your research projects, so that you can share updates, calls for participants, invite feedback on preliminary findings, announce events and list outputs (hopefully with as many as possible available in open access form). Consider including a section that provides resources such as links to other relevant websites and research groups, methods toolkits, curriculum ideas and reading lists.
  7. Take every opportunity to do interviews for mass media outlets and write pieces about your research for forums such as The Conversation.
  8. Make podcasts and videos to talk about your own research or interview other academics working in your area about their research.
  9. Don’t be afraid to self-cite in your publications (particularly if you are female – research shows that women academics are far less likely to cite their own work than are men).
  10. Use a platform like Slideshare to publish your presentation slides.

Edited to add: Also be aware that at times, increased visibility can bring with it unwanted negative attention, particularly if you research contentious or controversial topics that bring out the trolls, and if you are identify with a marginalised or vulnerable social group. If this is you, be careful in your choices about how to communicate your research publicly. (Thanks to Emma Renold for drawing attention to these issues when commenting on this post.)

Re/imagining Personal Data Workshop: Call for participants

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AoIR Preconference Workshop: Re/imagining Personal Data

  • Tuesday 1 October 2019, University of New South Wales, Sydney, Australia
  • 9.30 am-12.30 pm (followed by catered lunch)

Organisers: Deborah Lupton (UNSW Sydney), Larissa Hjorth (RMIT) and Annette Markham (Aarhus University)

Overview: This half-day workshop involves a selection of hands-on arts- and design-based activities to invite participants to re/imagine personal digital data. Participants will be able to experiment with innovative methods of eliciting creative and more-than-representational responses to personal data and generating speculative imaginaries about the futures of data. These methods can be used for teaching purposes or research projects.

We will be using these activities to explore and respond to these key questions:

  • What do personal data do?
  • How best can we use them?
  • What is our relationship with our personal data?
  • Which data do we want to keep and protect and which do we want to discard or forget?
  • What are our affective and sensory engagements with these data?
  • What are the futures of personal data?

Participants at all levels of research experience are invited to attend, including postgraduate students and people working outside the university sector.

Registration and lunch are free, but places are strictly limited.

Please contact Deborah Lupton, Faculty of Arts & Social Sciences, UNSW Sydney (d.lupton@unsw.edu.au ) as soon as possible with an email noting that you’d like to register to secure your place.

Please note that this workshop follows the Data Futures conference, 30 September 2019, also to be held at UNSW Sydney (details here), and precedes the Association of Internet Researchers Conference taking place in Brisbane (details here).

Photo credit: “I Love Data” She Wept. Bixtentro, Flickr. CC BY 2.0

Vitalities Lab is go!

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It’s been a busy few weeks as I’ve moved to my new position as SHARP Professor in the Faculty of Arts & Social Sciences, University of New South Wales, Sydney. I am attached to both the Centre for Social Research in Health and the Social Policy Research Centre in the Faculty. But I’ve also established my own little research entity: the Vitalities Lab (click here for details).

I’ll be recruiting team members for the Lab very soon. I have a doctoral scholarship and postdoc positions to fill, and also have funds to support international visiting fellows.

The title of the Lab was chosen to encapsulate my hopes and plans for what we will do. ‘Vitalities’ points to engaging in lively social research methods, inspiring creativity, new directions, excitement and passion in research. It is also a nod to the new materialism theoretical perspectives with which the Lab will be engaging – particularly the vital materialism perspective espoused in the work of scholars such as Jane Bennett, Rosi Braidotti, Karen Barad and Donna Haraway. Vitalities further refers to the topics we’ll be exploring, which will be about human/nonhuman life itself: initially, people’s experiences with digital health technologies; living with data; and digital food cultures.

We will be running methods workshops, reading groups and other events.

Do get in contact if you’d like to learn more, make a visit to chat, start a postgraduate research degree with us, or otherwise collaborate in lively doings: d.lupton@unsw.edu.au

 

Image attribution: ‘Scattered light at Northern Spark’ by Tony Webster, Flickr, CC BY 2.0

My publications in 2018

Books

  • Lupton, D. (2018) Fat (revised 2nd edition). London: Routledge.

Book chapters

  • Lupton, D. (2018) Lively data, social fitness and biovalue: the intersections of health self-tracking and social media. In Burgess, J., Marwick, A. and Poell, T. (eds), The Sage Handbook of Social Media. London: Sage, pp. 562-578.
  • Lupton, D. (2018) Digital health and health care. In Scambler, G. (ed), Sociology as Applied to Health and Medicine, 2nd Houndmills: Palgrave, pp. 277-290.
  • Lupton, D. and Smith, GJD. (2018) ‘A much better person’: the agential capacities of self-tracking practices. In Ajana, B. (ed), Metric Culture: Ontologies of Self-Tracking Practices. London: Emerald Publishing, pp. 57-75.
  • Lupton, D. (2018) 3D printing technologies: a third wave perspective. In Michael Filimowicz, M. and Tzankova, V. (eds), New Directions in Third Wave HCI (Volume 1, Technologies). Springer: London, pp. 89-104.

Journal articles

Encyclopedia entry

Have large numbers of Australians left Facebook? It seems not

I am currently working on analysing interviews from my newest research project ‘Facebook and Trust’. This project was designed in response to the huge publicity given to the Facebook/Cambridge Analytica scandal in March this year. I was interested in investigating how Australian Facebook users were using the platform in the wake of the scandal and what their feelings were about how Facebook make use of the personal information that is uploaded.

Following the scandal, numerous news reports claimed that large numbers of Australians were deleting their Facebook accounts as part of the #DeleteFacebook trend. As one report contended,

Many Australians are for the first time discovering just how much Facebook knows about them and many are shocked, leading them to quit the platform.

A Pew survey of US adults conducted soon after Cambridge Analytica found that around a quarter of respondents had deleted the Facebook app from their phone in the past 12 months, and more than half had adjusted their privacy settings  The survey did not ask directly about why the respondents had taken these measures, and as the time-frame related to the past year there may have been other reasons that these respondents had taken these actions (for example, different controversies over ‘fake news’ or poor content moderation on Facebook that have also received high levels of news media publicity).

Indeed, it is interesting to compare these findings with a previous Pew survey undertaken at the end of 2012, in which over two-thirds of the respondents who were current Facebook users said that they had sometimes voluntarily taken a break from using the platform and one-fifth who said they were not current Facebook users had used the platform at one time but had stopped using it. Those who had taken an extended break or had stopped using Facebook referred to reasons such as not wanting to expend too much time on the platform or finding the content overly personal, trivial or boring. As this survey suggests, some Facebook users have long had ambivalent feelings about using the platform.

There are no reliable statistics that I can find on how many Australians have deleted their Facebook account post-Cambridge Analytica. According to the Social Media Statistics Australia website, which provides a monthly report on Australians’ use of social media, in September 2018 approximately 60% of Australians (across the total population, including children) were active Facebook users, and 50% of Australians were logging on once a day. A similar proportion of Australians were regular YouTube users: both platforms had 15 million active monthly users. Next in order of popularity were Instagram (9 million users per month), Snapchat (6.4 million), WhatsApp (6 million), Twitter (4.7 million), LinkedIn (4.5 million) and Tumblr (3.7 million).

In terms of age breakdown, the site reports that in September 2018, Australians aged 25 to 39 years were the largest group of Facebook users (6.1 million), followed by those aged 40 to 55 (4.1 million), 18 to 25 (3.5 million), 55 to 64 (1.6 million) and 65 years and over (1.2 million). Less than a million of Australians aged 13 to 17 years used Facebook,

I compared the report for February 2018 (the month before the Cambridge Analytica scandal was publicised) and May 2018 (soon after the scandal) with the figures for September 2018. The website reports that in both February and May 2018, there were 15 million monthly active Australian users, just as there were for September 2018. So if large numbers of Australians have deleted their accounts, this is not showing up in these data.

The interviews I am currently analysing should cast some light on how Australian Facebook users have responded (if at all) to the Cambridge Analytica scandal and other privacy-related issues concerning the personal information they upload to Facebook. I’ll provide an update on the findings once I finish working through the interviews.

Personal data metaphors and imagery

I am currently completing my new book, with the working title of Data Selves, to be published by Polity. Here is an excerpt from a chapter that looks at personal data materialisations.

We have to work hard to find figures of speech and ways of thinking to encapsulate the ontology of digital data. The concept of digital data, a first glance, appears to describe a wholly immaterial phenomenon that does not engage the senses: there seems to be nothing to look at, touch, hear, smell or taste. The metaphors and other figures of language employed to describe digital data are attempts to conceptualise and make sense of these novel forms of information and their ontologies. Even as digital technologies continue to generate and process detailed information about people’s bodies, social relationships, emotions, practices and preferences, prevailing discourses on these data tend to de-personalise and de-humanise them. The use of the term ‘data’ to describe these details signals a way of viewing and treating them, presenting these aspects as raw materials, ripe for processing and exploitation to make them give up their meaning (Räsänen and Nyce 2013; Gitelman and Jackson 2013). Once they have become defined and labelled as ‘data’, these details about people’s lives tend to be imagined as impersonal, scientific and neutral. They have been extracted from their embodied, sensory and affective contexts, rendered into digitised formats and viewed as material for research, management or commercial purposes.

The term ‘data’ is closely associated with ‘information’. Information as a term is subject to a wide range of (often debated) definitions in the academic literature. It usually involves the assumption that there are structures, correlations and patterns involved in the organisation and communication of meaning. Information tends to be imbued with the pragmatic meanings of rational thought-processes and material that can contribute to acquiring and using knowledge. It has use and value based on these attributes (Buckland 1991). Digital data, as forms of information that have been collected and processed using digital technologies, are often portrayed as more accurate and insightful than many other information sources (Lupton 2015; Kitchin 2014). Many references to big data represent it as anonymised massive collections of details that are valuable commodities, open to profitable exploitation. The World Economic Forum’s report (2011) describing big data as ‘the new oil’, ‘a valuable resource of the 21st century’ and a ‘new asset class’ is an influential example of this metaphor.

Metaphors of fluidities also tend to be employed when describing digital data. Digital data are popularly imagined to stream, flow and circulate in the ephemeral digital data economy, emitting imperceptibly from digital devices, flying through the air to lodge in and move between computing clouds as if comprised of vaporised water. Many metaphors of digital data use words and phrases that denote overwhelming power and mobilities, again often referring to large bodies of uncontrollable water; the data ‘deluge’, ‘flood’, ‘ocean’ and even ‘tsunami’ that constantly appear in popular accounts of big data in particular. These figures of speech are used to denote feelings of being overwhelmed by large, powerful masses of data (‘big data’) that appear to be difficult to control or make sense of in their volume. Still other metaphors represent data as ‘exhaust’, ‘trails’ or ‘breadcrumbs’, denoting the by-products of other interactions on digital networks. These metaphors suggest a tangible, perceivable form of digital data, albeit tiny, that require effort to discern and give up their value (Lupton 2015).

The terms ‘clean’ and ‘dirty’ have long been used in descriptions of data, however these data are generated. These terms refer to the degree to which the data can be used for analysis: clean data are ready for use, dirty data sets require further processing because they are incomplete, outdated, incorrect or obsolete. Portrayals of the affordances of digital data on the body/self, in their emphasis on objectivity and neutrality – or what might be described as their ‘cleanliness’ – denote a view of information about oneself that privileges such ‘clean’ data over what might be contrasted as the ‘dirty’ data that the body produces from sensual experience. Human cognition, memory, perception and sensation are ‘weak’ because they are ‘unscientific’. They are borne of fallible fleshly embodiment rather than the neutral, objective data that are generated by computer software and hardware.

Data have also been referred to as ‘raw’, suggesting that they are materials that are untouched by culture. It is assumed that by working on ‘raw’ data, data scientists transform these materials into useable commodities. Part of this transformation may involve ‘cleaning’ ‘dirty data’. Boellstofff (2013) uses the term ‘rotted data’ to describe the ways in which the materiality of data can degrade (for example, damaged hard drives that store data), but also how data can be transformed in unplanned or accidental ways that do not follow algorithmic prescriptions. Here again, these metaphors of ‘raw’, ‘cooked’ and ‘rotted’ draw attention the materiality of data and the processing, deterioration and recuperation that are part of human-data assemblages.

In her essay on digital data, Melissa Gregg (2015) employs a number of other metaphors that she devised to encapsulate the meanings of data. Data ‘agents’ suggests the capacities of data to work with algorithms to generate connections: matches, suggestions and relationships between social phenomena that otherwise would not be created. Gregg gives the examples of recommendation sites and online dating services, which connect strangers and their experiences with each other in ways that were previously unimaginable. She goes on to suggest that ‘In these instances, data acts [sic] rather more like our appendage, our publicist, even our shadow’ (Gregg 2015). Gregg also employs the metaphor of data ‘sweat’ (another liquid metaphor) in the attempt to emphasise the embodied nature of data, emerging or leaking from within the body to the outside in an uncontrolled manner to convey information about that body, including how hard it is working or how productive it is. Data ‘sweat’, therefore, can be viewed as a materialisation of labour. She then suggests the concept of data ‘trash’ (similar to the ‘exhaust’ metaphor mentioned above). Data ‘trash’ is data that is in some way useless or potentially polluting or hazardous: Gregg links this metaphor with the environmental effects generated by creating, storing and processing data in data centres. Both the metaphors of data ‘sweat’ and ‘trash’ suggest the materiality of digitised information as well as its ambivalent and dynamic status as it moves between ascriptions of high value and useless or even disgusting by-product.

An analysis of images used to represent big data in online editions of The New York Times and The Washington Post (Pentzold et al. 2018) found that they tended to fall into several categories in the attempt to visually represent big data: using large-scale numbers, interpretive abstract renditions, showing numbers or graphs on smartphone or computer screens, images of data warehouses and devices that generate data, robots, datafied individuals and meteorological imagery such as clouds. A dominant visual image involved photographic images of people working in the big data industry, such as data scientists, ‘nerds’ and ‘geeks’ (overwhelmingly male) and logos of internet companies. These images served as visual surrogates to represent the immateriality of big data. The researchers compared these images with those found on a general Google image search for ‘big data’ and also on Wikipedia and the image platforms Fotolia, Flickr and Pinterest. They noted that the images they found on these platforms were very homogeneous, featuring the colour blue, the words ‘big data’ written large, binary numbers, network structures and surveillant human eyes. These kinds of descriptions suggest that big datasets (including those drawn from people’s lives and experiences) are natural resources that are unproblematically open to exploration, mining and processing for profit. The personal details about people contained within these massive datasets are reimagined as commodities or research material. It is telling that the human elements of these images largely include men working in data analytics rather than the range of people who generate data or who may make use of their own data as part of their everyday lives.

In these types of portrayals, the status of personal data as human, or at least partly human entities is submerged in the excitement about how best to exploit these details as material commodities. Their liveliness is represented in ways that suggest their economic potential as nonhuman organic materials (streams, flows, oil, clouds, breadcrumbs). Yet conversely, another dominant discourse about personal data, which is particularly promulgated by the data profiling industry and civil society privacy advocates, is that these details are all-too-human or even excessively human: intensely intimate and revealing of people’s uniquely human characteristics. Proponents of the ‘Internet of Me’ make claims such as:

Now imagine tech working in your body at the biological level. Your body could express itself on its own, without you having to be in charge, to deliver more happiness, better health, whatever you truly need and want.

These sociotechnical imaginaries position devices and data as working together with human bodies in ways that devolve agency to the device. ‘You’ no longer have to be ‘in charge’ – instead, the device takes over. Other imaginaries around the Internet of Me configure the idea of personal cloud computing, in which all people’s personal data go to a centralised cloud computing repository where they will be able to access all their data.

When I performed my own Google image search using the term ‘personal data’, the images that were returned by the search again featured the colour blue, male figures and binary numbers. Notably, several images showed a pen and a paper form with the words ‘personal information’ at the top, perhaps as an attempt to respond to the immateriality of digitised information by rendering it in analogue forms with which many people would be familiar. Images using locks and keys as metaphors were also dominant, suggesting the value of personal data but also how closed they are to people who may want to make use of them. When I used the search term ‘personal data privacy’, new images were introduced in addition to those appearing under ‘personal data’. These included images of spy-like or Big Brother surveillance figures and also images showing human hands protectively attempting to cover computer keyboards or screens, as if to elude the gaze of these spying figures as people used their devices.

One online article on the Internet of Me features an image in which a human body is comprised of many different social media and other internet platform icons as well as coloured dots representing other data sources. Instead of an assemblage of flesh-bone-blood, the body is completely datafied and networked. The interesting thing is that this body is represented as an autonomous agent. The networks that generate data and keep the body vibrant and functioning are internal, not externalised to networks outside this socially alienated body. Data flows are contained within elements of the body rather than leaking outside it to other bodies. This suggests an imaginary in which the Internet of Me is neatly contained within the envelope of the body/self and thus able to control ingress and egress. This is an orderly closed system, one that confounds both utopian and dystopian imaginaries concerning the possibilities and risks of one’s body/self being sited as just one node in vast and complex networked digital system.

In contrast, a series of 2018 British advertisements for the BBH London & Experian data analytics company used the ‘data self’ concept in an attempt to humanise data profiling and emphasise the similarities of these profiles to the people from whom they are generated. Six versions of this ad featured photographs of comedian Marcus Brigstoke and his ‘data self’, a person who looked exactly like him. As one of the ads, headlined ‘Meet your Data Self’ claimed: ‘Your Data Self is the version of you that companies see when you apply for things like credit cards, loans and mortgages. You two should get acquainted’. One of the ads, headlined, ‘What shape is your Data Self in?’, showed the comedian looking at his doppelganger lifting a heavy barbell. The copy read ‘If your Data Self looks good to lenders, you’re more likely to be approved for credit. That’s a weight off. Get to know your Data Self at Experian.com.uk.’ Another ad asked ‘Is your Data Self making the right impression?’, depicting the comedian, dressed in casual clothes, shaking hands with his more formally dressed (in suit and tie) data self.  Notably, this person and his ‘data self’ was a white, youngish man, excluding representatives from other social groups.

The ontological status of personal data, therefore, constantly shifts in popular representations between human and nonhuman, valuable commodity and waste matter, nature and culture, productive and dangerous. In both modes of representation, the vibrancies of digital data – their ceaseless production, movements, leakages – are considered to be both exciting and full of potential but also as dangerous and risky. Personal data assemblages are difficult to control or exploit by virtue of their liveliness.

References

Boellstorff, T. (2013). Making big data, in theory. First Monday, 18(10).

Buckland, M. K. (1991). Information as thing. Journal of the American Society for Information Science, 42(5), 351.

Gitelman, L., & Jackson, V. (2013). Introduction. In L. Gitelman (Ed.), Raw Data is an Oxymoron (pp. 1-14). Cambridge, MA: MIT Press.

Gregg, M. (2015). The gift that is not given. In T. Boellstorff, & B. Maurer (Eds.), Data, Now Bigger and Better! (pp. 47-66). Chicago: Prickly Paradigm.

Kitchin, R. (2014). The Data Revolution: Big Data, Open Data, Data Infrastructures and Their Consequences. London: Sage.

Lupton, D. (2015). Digital Sociology. London: Routledge.

Pentzold, C., Brantner, C., & Fölsche, L. (2018). Imagining big data: Illustrations of “big data” in US news articles, 2010–2016. New Media & Society, online first.

Räsänen, M., & Nyce, J. M. (2013). The raw is cooked: data in intelligence practice. Science, Technology & Human Values, 38(5), 655-677.

World Economic Forum (2011). Personal Data: The Emergence of a New Asset Class. World Economic Forum.