Leeds University Library

SLSP3242
The Social Life of Data Module Reading List

The Social Life of Data, 2017/18, Semester 1
Dr Rosemary Hill
R.L.Hill@leeds.ac.uk
Tutor information is taken from the Module Catalogue

Learning Resources and Key Readings

There is no compulsory textbook for this module. You will be expected to read widely using the references supplied, and must come to the tutorial prepared to discuss the key readings set for that week. Other references are supplied for further reading and essay preparation.

The following book provides a good overview of some of the themes we will be discussing, but it is not exhaustive and you should follow your interests:

Kitchin, R. 2014. The data revolution : big data, open data, data infrastructures & their consequences. London: Sage.

The following journals contain many relevant articles:

· Ada: A Journal of Gender, New Media & Technology http://adanewmedia.org

· Big data and society ISSN: 2053-9517 http://bds.sagepub.com/

· First Monday [electronic resource]. ISSN: 1396-0466 http://firstmonday.org

· Information visualization. ISSN: 1473-8716 http://ivi.sagepub.com/

· Information, communication and society. ISSN: 1369-118x http://www.tandfonline.com/toc/rics20/current

· New media and society. ISSN: 1461-4448 http://nms.sagepub.com/

· Surveillance & society [electronic resource]. ISSN: 1477-7487 http://surveillance-and-society.org/

· Television & New Media ISSN: 1527-4764 http://tvn.sagepub.com/

· Theory, culture & society. ISSN: 0263-2764 http://tcs.sagepub.com/

Relevant articles appear in other sociology, media studies, geography and computer science journals too so use the library’s search function and google scholar to find these.

Top of page

Topic 1 : What is data?

Key Reading

Kitchin, R. 2014. The data revolution : big data, open data, data infrastructures & their consequences. London: Sage. – Note, Preface and Introduction

Porter, T.M. 1995. Trust in numbers : the pursuit of objectivity in science and public life ISBN: 0691037760. Princeton: Princeton University Press. – Preface and Introduction

van Dijck, J. 2014. Datafication, dataism and dataveillance: Big Data between scientific paradigm and ideology. Surveillance & society [electronic resource]. ISSN: 1477-7487. 12(2), pp.197-208.

Further Reading

Barnes, T.J. 2013. Big data, little history. Dialogues in Human Geography. 3 (3), pp.297-302.

Beer, D. 2013. Popular culture, digital archives and the new social life of data. Theory, culture & society. ISSN: 0263-2764. 30(4), pp.47-71.

Beer, D. 2016. Metric power ISBN: 9781349717682 (pbk.) : £66.99; 9781137556486 (hbk.) : £63.00; 9781137556493 (ebook). Basingstoke: Palgrave Macmillan.

Beer, D. 2016. How should we do the history of Big Data? Big data and society, 3 (1).

Bollier, D. 2010. The promise and peril of big data. Washington, D.C.: Aspen Institute, Communications and Society Program. - Available online: https://www.emc.com/collateral/analyst-reports/10334-ar-promise-peril-of-big-data.pdf

boyd, D., & Crawford, K. 2012. Critical questions for Big Data: Provocations for a cultural, technological, and scholarly phenomenon. Information, communication and society. 15(5), 662-679.

Day, R. E. 2008. The modern invention of Information : discourse, history, and power.. Carbondale: Southern Illinois University Press

Ekbia, H. et al. 2015. Big data, bigger dilemmas: A critical review. Journal of the Association for Information Science and Technology. 66(8), pp.1523-1545.

Gitelman, L. and Jackson, V. 2013. Introduction. In: Gitelman, L. ed. "Raw data" is an oxymoron [electronic resource]. Cambridge, MA: MIT Press, pp.1-14.

Gitelman, L. 2014. Paper knowledge : toward a media history of documents. London: Duke University Press.

Hacking, I. 1990. The taming of chance. Cambridge: Cambridge University Press.

Haraway, D. 1988. Situated knowledges: The science question in feminism and the privilege of partial perspective. Feminist Studies. ISSN: 0046-366314(3), pp.575-599.

Haraway, D. J. 1991. Simians, cyborgs, and women: the reinvention of nature. New York: Routledge. Chapter: A cyborg manifesto: science, technology, and socialist-feminism in the late twentieth century. http://faculty.georgetown.edu/irvinem/theory/Haraway-CyborgManifesto-1.pdf

Kitchin, R. 2014. The data revolution : big data, open data, data infrastructures & their consequences. London: Sage.

Manovich, L. 2011. Trending: the promises and the challenges of big social data. In: Gold, M.K. ed. Debates in the digital humanities. Minneapolis: University of Minnesota Press.

Markham, A.N. 2013. Undermining 'data': A critical examination of a core term in scientific inquiry. First Monday [electronic resource].. 18 (10).

Mayer-Schönberger, V. and Cukier, K. 2013. Big data: a revolution that will transform how we live, work, and think. Boston, Mass: Houghton Mifflin Harcourt.

Michael, M. and Lupton, D. 2015. Toward a manifesto for the “public understanding of big data”. Public understanding of science.. 25 (1), pp.104-116.

Open Data Institute. n.d. What is open data? [Online]. Available from: https://theodi.org/what-is-open-data.

Pawson, R. 1989. A measure for measures : a manifesto for empirical sociology ISBN: 0415026598 (pbk ; cased) : £10.95; 0415028701. London: Routledge.

Porter, T.M. 1995. Trust in numbers : the pursuit of objectivity in science and public life. Princeton: Princeton University Press.

Rosenberg, D. 2013. Data before the fact. In: Gitelman, L. ed. "Raw data" is an oxymoron [electronic resource]. Cambridge, MA: The MIT Press, pp.15-40.

Stanley, L. and Wise, S. 1993. Breaking out again : feminist ontology and epistomology. 2nd ed. London: Routledge.

van Dijck, J. 2014. Datafication, dataism and dataveillance: Big Data between scientific paradigm and ideology. Surveillance & society [electronic resource].. 12 (2), pp.197-208.

Top of page

Topic 2: Big data giddiness

Key Reading

Gurstein, Michael B. 2011. "Open data: Empowering the empowered or effective data use for everyone? " First Monday [electronic resource]. Jan.

Kitchin, R. (2014). The data revolution : big data, open data, data infrastructures & their consequences. London: Sage. – Open and Linked Data

For discussion

Anderson, C. 2008. The end of theory. [Online]. Available from: http://www.wired.com/science/discoveries/magazine/16-07/pb_theory.

Further Reading

Baack, S. 2015. Datafication and empowerment: how the open data movement re-articulates notions of democracy, participation and journalism. Big data and society. 2 (2).

Bartlett, J. and Tkacz, N. 2014. Keeping an eye on the dashboard. Demos Quarterly. [Online]. (4). Available from: http://quarterly.demos.co.uk/article/issue-4/keeping-an-eye-on-the-dashboard/.

Beer, D. 2016. Metric power ISBN: 9781349717682 (pbk.) : £66.99; 9781137556486 (hbk.) : £63.00; 9781137556493 (ebook). Basingstoke: Palgrave Macmillan.

Boyd, d. 2016. Undoing the neutrality of big data. Florida Law Review ISSN: 1045-4241 Forum. 67.

Burrows, R. 2012. Digitalization, Visualization and the 'Descriptive Turn' in Contemporary Sociology. In: Heywood, I. and Sandywell, B. eds. The handbook of visual culture ISBN: 9781847885739 (hbk.) : £80.00; 184788573X (hbk.) : £80.00.  London: Berg, pp.572-588.

Cohen, R.L. 2016. Towards a quantitative feminist sociology. In: McKie, L. and Ryan, L. eds. An end to the crisis of empirical sociology? : trends and challenges in social research. Abingdon: Routledge, pp.117-135.

Ferrer-Conill, R. 2017. Quantifying journalism? A study on the use of data and gamification to motivate journalists. Television & New Media ISSN: 1527-4764. Online.

Gabrys, J., Pritchard, H. and Barratt, B. 2016. Just good enough data: Figuring data citizenships through air pollution sensing and data stories. Big data and society ISSN: 2053-9517. 3(2).

Levy, K.E.C. and Johns, D.M. 2016. When open data is a Trojan Horse: The weaponization of transparency in science and governance. Big data and society ISSN: 2053-9517. 3(1).

Kennedy, H., & Hill, R. L. 2016. The pleasure and pain of visualising data in times of data power Television & New Media ISSN: 1527-4764. Online.

Mayer-Schönberger, V. and Cukier, K. 2013. Big data: a revolution that will transform how we live, work, and think. Boston, Mass: Houghton Mifflin Harcourt.

Porter, T. M. 1995. Trust in numbers : the pursuit of objectivity in science and public life. Princeton: Princeton University Press.

Purohit, H. et al. 2016. Gender-based violence in 140 characters or fewer: A #BigData case study of Twitter. First Monday [electronic resource].. 21 (1-4).

Rieder, G., & Simon, J. 2016. Datatrust: Or, the political quest for numerical evidence and the epistemologies of Big Data. Big data and society. 3 (1).

Schrock, A. and Shaffer, G. 2017. Data ideologies of an interested public: A study of grassroots open government data intermediaries. Big data and society ISSN: 2053-9517. 4(1).

Scott, J. 2010. Quantitative methods and gender inequalities. International journal of social research methodology.. 13 (3), pp.223-236.

van der Velden, Lonneke. 2015. "Forensic devices for activism: metadata tracking and public proof." Big data and society 2(2), pp.1-14.

Welles, B.F. 2014. On minorities and outliers: The case for making Big Data small. Big data and society. 1(1).

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Topic 3: Populations, states and data

Key Reading

Bulmer, M., Bales, K. and Kish Sklar, K. eds. 2011. The social survey in historical perspective 1880-1940. Cambridge: Cambridge University Press. Chapter 1.

Lazarsfeld, P.F. 1961. Notes on the History of Quantification in Sociology--Trends, Sources and Problems. Isis.: A Journal of the History of Science Society. 52 (2), pp.277-333.

Special Topic: Women’s Work in 19th Century Census

Alexander, S., Davin, A. and Hostettler, E. 1979. Labouring Women: a reply to Eric Hobsbawm. History workshop journal.. 8 (1), pp.174–182.

Higgs, E. 1987. Women, Occupations and Work in the Nineteenth-century Censuses. History workshop journal.. 23, pp.59–80.

Higgs, E. and Wilkinson, A. 2016. Women, Occupations and Work in the Victorian Censuses Revisited. History workshop journal.. 81, pp.17–38.

Further Reading

Buck, P. 1977. Seventeenth-Century Political Arithmetic: Civil Strife and Vital Statistics. Isis.: A Journal of the History of Science Society. 68 (1), pp.67-84.

Buck, P. 1982. People Who Counted: Political Arithmetic in the Eighteenth Century. Isis.: A Journal of the History of Science Society. 73 (1), pp.28-45.

Callebaut, W. 2012. Scientific perspectivism: A philosopher of science’s response to the challenge of big data biology. Studies in history and philosophy of biological and biomedical sciences. 43(1), pp.69-80.

Desrosières, A. 1998. The politics of large numbers : a history of statistical reasoning. Cambridge, MA: Harvard University Press.

Gitelman, L.e. 2013. "Raw data" is an oxymoron [electronic resource]. Cambridge, MA: MIT Press.

Hacking, I. 1990. The taming of chance. Cambridge: Cambridge University Press.

Hakim, C. 1985. Social monitors: population censuses as social surveys . In: M. Bulmer. ed. Essays on the history of British sociological research. Cambridge: Cambridge University Press, pp.39-51 .

Haraway, D. 1988. Situated knowledges: The science question in feminism and the privilege of partial perspective. Feminist Studies.. 14(3), pp.575-599.

Harding, S.G. 1986. The science question in feminism. Milton Keynes: Open University Press.

Hide, W. et al. 2008. Big data The future of biocuration. Nature.. 455(7209), pp.47-50.

Higgs, E. 2001. The Rise of the Information State: the Development of Central State Surveillance of the Citizen in England, 1500–2000. Journal of historical sociology.. 14 (2), pp.175-197.

Higgs, E. 2004. The information state in England : the central collection of information on citizens since 1500. Basingstoke: Palgrave Macmillan.

Rosenberg, D. 2013. Data before the fact. In: Gitelman, L. ed. "Raw data" is an oxymoron [electronic resource]. Cambridge, MA: The MIT Press, pp.15-40.

Salsburg, D. 2001. The lady tasting tea : how statistics revolutionized science in the twentieth century. New York: McDougal W. H. Freeman and Company.

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Topic 4: Algorithms and gender, race, class

Key Reading

Bivens, R. 2015. The gender binary will not be deprogrammed: Ten years of coding gender on Facebook. New media and society.. 19(6), pp.880-898.

Kitchin, R. 2016. Thinking critically about researching algorithms. Information, communication and society.. 20(1), pp.14-29.

Lam, B. 2015. For More Workplace Diversity, Should Algorithms Make Hiring Decisions? [Online]. Available from: http://www.theatlantic.com/business/archive/2015/06/algorithm-hiring-diversity-HR/396374/ .

Naughton, J. 2016. Even algorithms are biased against black men [Online]. Available from: https://www.theguardian.com/commentisfree/2016/jun/26/algorithms-racial-bias-offenders-florida.

Key Watching

Crawford, K. 2013. Algorithmic illusions: the hidden biases of Big Data. In: Strata, Santa Clara, CA. Available from: https://www.youtube.com/watch?v=irP5RCdpilc. Video.

Further Reading

Amoore, L. 2009. Algorithmic War: Everyday Geographies of the War on Terror. Antipode.. 41 (1), pp.49-69.

Barocas, S., Hood, S. and Ziewitz, M. 2013. Governing algorithms: a provocation piece. [Online]. Available from: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2245322.

Bassett, C. 2013. Feminism, Expertise and the Computational Turn. In: Thornham, H. and Weissmann, E. eds. Renewing feminisms : radical narratives, fantasies and futures in media studies. New York: I.B.Tauris, pp.199-215.

Beer, D. 2016. The social power of algorithms. Information, communication and society.. 20(1), pp.1-13.

Beer, D. 2016. Metric power. Basingstoke: Palgrave Macmillan.

Bivens, R. 2015. Under the Hood: The Software in Your Feminist Approach. Feminist Media Studies. 15 (4), pp.714-717.

boyd, d. 2016. Undoing the neutrality of big data. Florida Law Review ISSN: 1045-4241 Forum. 67, pp.226-232.

boyd, d., Levy, K. and Marwick, A.E. 2014. The networked nature of algorithmic discrimination. In: Gangadharan, S.P. and Eubanks, V. eds. Data & Discrimination: Collected Essays.  Open Technology Institute; New America, pp.53-57. - Available online: https://www.ftc.gov/system/files/documents/public_comments/2014/10/00078-92938.pdf

Bucher, T. 2016. The algorithmic imaginary: exploring the ordinary affects of Facebook algorithms. Information, communication and society.. online.

Cheney-Lippold, J. 2011. A New Algorithmic Identity: Soft Biopolitics and the Modulation of Control. Theory, culture & society.. 28 (6), pp.164-181.

Couldry, N. and Powell, A. 2014. Big Data from the bottom up. Big data and society ISSN: 2053-9517. 1(2).

Couldry, N., Fotopoulou, A. and Dickens, L. 2016. Real social analytics: A contribution towards a phenomenology of a digital world. The British journal of sociology. ISSN: 0007-1315. 67(1), pp.118-137.

Crawford, K. 2013. The hidden biases in big data. [Online]. Available from: http://blogs.hbr.org/2013/04/the-hidden-biases-in-big-data/.

Gillespie, T. 2016. Algorithmically recognizable: Santorum’s Google problem, and Google’s Santorum problem. Information, communication and society.. 20(1), pp.63-80.

Hu, M. 2015. Big data blacklisting. Florida Law Review. 67, pp.1735-1809.

Kitchin, R. 2016. Thinking critically about researching algorithms. Information, communication and society. ISSN: 1369-118x. 20(1), pp.14-29.

Mager, A. 2012. Algorithmic ideology. Information, communication and society.. 15 (5), pp.769-787.

Robinson + Yu. 2014. Civil rights, big data and our algorithmic future. [Online]. Available from: https://bigdata.fairness.io/.

Willson, M. 2016. Algorithms (and the) everyday. Information, communication and society.. 20(1), pp. 137-150.

Yeung, K. 2016. ‘Hypernudge’: Big Data as a mode of regulation by design. Information, communication and society.. 20(1), pp.118-136.

Social Media Collective. 2011-2016. Critical algorithm studies: a reading list. [Online]. Available from: https://socialmediacollective.org/reading-lists/critical-algorithm-studies/.

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Topic 5: The quantified self

Key Reading

Haggerty, K.D. and Ericson, R.V. 2000. The surveillant assemblage. The British journal of sociology. ISSN: 0007-1315. 51(4), pp.605-622.

Till, C. 2014. Exercise as labour: quantified self and the transformation of exercise into labour. Societies. 4, pp.446-462.

Whitson, J. R. 2013. Gaming the quantified self. Surveillance & society [electronic resource].. 11(1/2), pp.163-176.

Further reading

Becker, B.W. 2014. The Quantified Self: Balancing Privacy and Personal Metrics. Behavioral & social sciences librarian. 33 (4), pp.212-215.

Copelton, D. A. 2010. Output that counts: pedometers, sociability and the contested terrain of older fitness walking. Sociology of health and illness.. 32(2), pp.304-318.

Crawford, K., Lingel, J. and Kappie, T. 2015. Our metrics, ourselves: a hundred years of self-tracking from the weight scale to the wrist wearable device. European Journal of Cultural Studies. 18(4), pp.479-496.

Fotopoulou, A. and O'Riordan, K. 2017. Training to self-care: fitness tracking, biopedagogy and the healthy consumer. Health sociology review ISSN: 1446-1242. 26(1), pp.54-68.

Hoy, M.B. 2016. Personal Activity Trackers and the Quantified Self. Medical reference services quarterly. 35 (1), pp.94-100.

Lomborg, S. and Frandsen, K. 2015. Self-tracking as communication. Information, communication and society.. 19(7), pp. 1015-1027.

Lupton, D. 2013. Quantifying the body: monitoring and measuring health in the age of mHealth technologies. Critical public health.. 23(4), pp.393-403.

Lupton, D. 2013. Understanding the human machine. IEEE technology and society magazine.. (Winter 2013), pp.25-30.

Lupton, D. 2014. Digital sociology. Abingdon: Routledge.

Lupton, D. 2016. The quantified self : a sociology of self-tracking. Malden, MA: Polity Press.

Lupton, D. 2015. Quantified sex: a critical analysis of sexual and reproductive self-tracking using apps. Culture, health & sexuality.: An International Journal for Research, Intervention and Care. 17(4), pp.440-453.

Lupton, D. and Jutel, A. 2015 It’s like having a physician in your pocket! A critical analysis of self-diagnosis smartphone apps. Social science & medicine.. 133, pp.128-135.

Mekky, S. 2014. Wearable Computing and the Hype of Tracking Personal Activity. SIDER. Royal Institute of technology, Stockholm, Sweden. - Available online: http://sider2014.csc.kth.se/wp-content/uploads/sites/8/2014/04/sider14_submission_22.pdf

Millington, B. 2014. Smartphone apps and the mobile privatisation of health and fitness. Critical studies in media communication. 31(5), pp.479-493.

Mol, A. 2009. Living with diabetes: care beyond choice and control. Lancet.. 373, pp.1756-1757.

Moore, P. and Robinson, A. 2015. The quantified self: What counts in the neoliberal workplace. New media and society.. 18(11), pp.2774-2792.

O'Riordan, K. 2013. Biodigital Publics: Personal Genomes as Digital Media Artefacts. Science as culture. ISSN: 0950-5431. 22(4), pp.516-539.

Pantzar, M. and Ruckenstein M. 2014. The heart of everyday analytics: emotional, material and practical extensions in self-tracking market. Consumption, markets & culture.. 18(1), pp. 92-109.

Ruckenstein, M. 2014. Visualized and interacted life: personal analytics and engagements with data doubles. Societies. 4 (1), pp.68-84.

Servick, K. 2015. Mind the phone. Science.. 350 (6266), pp.1306-1309.

Shilton, K. 2012. Participatory personal data: An emerging research challenge for the information sciences. Journal of the American Society for Information Science and Technology.. 63 (10), pp.1905-1915.

Swan, M. 2012. Sensor mania! The internet of things, wearable computing, objective metrics and the quantified self 2.0. Journal of sensor and actuator networks. 1, pp.217-253.

Thomas, G.M. and Lupton, D. 2015. Threats and thrills: pregnancy apps, risk and consumption. Health, risk and society.. 17(7-8), pp. 495-509.

Williams, S., Coveney, C. and Meadows, R. 2015. ‘M-apping’ sleep? Trends and transformations in the digital age. Sociology of health and illness.. 37(7), pp.1039-1054.

Williamson, B. 2015. Algorithmic skin: health-tracking technoloiges, personal analysis and the biopedagogies of digitized health and physical education. Sport, Education and Society.. 20(1), pp.133-151.

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Topic 6: Surveillance, security, and the border

Key Reading

Adey, P., 2012. Borders, identification and surveillance. In Ball, K., Haggerty, K., and Lyon, D., eds. 2012. Routledge handbook of surveillance studies [electronic resource]. Abingdon: Routledge .

Bauman, Z., Bigo, D., Esteves, P., Guild, E., Jabri, V., Lyon, D., and Walker, R., 2014. After Snowden: Rethinking the Impact of Surveillance. International Political Sociology. 8 (2), pp.121-144.

Bigo, D., 2006. Security, exception, ban and surveillance. In Lyon, D., ed. 2006. Theorizing surveillance : the panopticon and beyond. Cullompton: Willan Publishing.

Further Reading

Aas, K., Gundhus, H., and Lomell, H., eds. 2008. Technologies of insecurity : the surveillance of everyday life. Abingdon: Routledge.

Adey, P., 2004. Surveillance at the Airport: Surveilling Mobility/Mobilising Surveillance. Environment and planning. A : environment and planning.. 36(8), pp.1365-1380.

Adey, P., 2009. Facing airport security: affect, biopolitics, and the preemptive securitisation of the mobile body. Environment and planning. D : society and space.. 27 (2), pp.274-295.

Amoore, L., 2006. Biometric borders: Governing mobilities in the war on terror’, Political geography.. 25 (3), pp.336-351.

Amoore, L. 2009. Algorithmic War: Everyday Geographies of the War on Terror. Antipode.. 41 (1), pp.49-69.

Amoore, L. 2009. Lines of sight: on the visualization of unknown futures. Citizenship studies.. 13(1), pp.17-30.

Amoore, L., 2013. The politics of possibility : risk and security beyond probability. Durham: Duke University Press.

Ball, K., Haggerty, K., and Lyon, D., eds. 2012. Routledge handbook of surveillance studies [electronic resource]. Abingdon: Routledge.

Barnard-Wills, D., 2012. Surveillance and identity : discourse, subjectivity and the state. Farnham: Ashgate.

Beck, U., 1999. World risk society. Malden: Polity Press.

Dubrofsky, R.E. and Magnet, S.A. 2015. Feminist surveillance studies. Duke University Press.

French, M., 2014. Gaps in the gaze: Informatic practice and the work of public health surveillance. Surveillance & society [electronic resource]., 12 (2), pp.226-242.

Gandy, O., 1993. The panoptic sort : a political economy of personal information (Critical Studies in Communication & in Cultural Industries). Boulder: Westview Press.

Graham, S., and Wood, D., 2003. Digitizing surveillance: categorization, space, inequality. Critical social policy., 23 (2), pp.227-248.

Haggerty, K., and Ericson, R., 2000. The surveillant assemblage. The British journal of sociology.. 51( 4), pp.605-622.

Hier, S., 2004. Probing the Surveillant Assemblage: on the dialectics of surveillance practices as processes of social control. Surveillance & society [electronic resource]., 1 (3), pp.399-411.

Hope, A., 2005. Panopticism, play and the resistance of surveillance: case studies of the observation of student Internet use in UK schools. British journal of sociology of education., 26 (3), pp.359-373.

Lyon, D., 2003. Airports as Data Filters: Converging Surveillance Systems after September 11, Information, Communication and Ethics in Society, 1 (1), pp.13-20.

Lyon, D., ed. 2006. Theorizing surveillance : the panopticon and beyond. Cullompton: Willan Publishing.

Lyon, D., 2014. Surveillance, Snowden, and Big Data: Capacities, consequences, critique. Big data and society 1 (2), pp.1-13.

Marx, G., 2016. Windows into the soul : surveillance and society in an age of high technology. Chicago: The University of Chicago Press.

Ohm, P. 2010. Broken promises of privacy: Responding to the surprising failure of anonymization. UCLA Law Review. 57 (6), pp.1701-1777.

Raley, R. 2013. Dataveillance and countervailance. In: Gitelman, L. ed. "Raw data" is an oxymoron [electronic resource]. Cambridge, MA: The MIT Press, pp.121-146.

Russell Neuman, W., Guggenheim, L., Mo Jang, S., and Bae, S. Y. 2014. The dynamics of public attention: Agenda-setting theory meets Big Data. Journal of communication. 64(2), pp.193-214.

Tene, O. and Polonetsky, J. 2013. Big data for all: privacy and user control in the age of analytics. Northwestern Journal of Technology and Intellectual Property. 11 (5), p.239.

Tucker, P. 2013 Has big data made anonymity impossible? Cambridge: Technology Review. 116, pp.64-66.

Tufekci, Z. 2014. Engineering the public: Big Data, surveillance and computational politics. First Monday [electronic resource]. 19 (7).

Van Dijck, J. 2014. Datafication, dataism and dataveillance: Big Data between scientific paradigm and ideology. Surveillance & society [electronic resource].. 12 (2), pp.197-208.

Zuboff, S. 2016. The Secrets of Surveillance Capitalism. Frankfurter Allgemeine. 05/03/2016.http://www.faz.net/aktuell/feuilleton/debatten/the-digital-debate/shoshana-zuboff-secrets-of-surveillance-capitalism-14103616.html? printPagedArticle=true#pageIndex_2.

Zuboff, S. 2017. Master or Slave? : The Fight for the Soul of Our Information Civilization. New York: PublicAffairs.

Zureik, E., and Hindle, K., 2004. Governance, Security and Technology: the Case of Biometrics, Studies in political economy., 73 (1), pp.113-137.

Zureik, E., and Salter, M., eds. 2005. Global surveillance and policing : borders, security, identity. Cullompton: Willan Publishing.

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Topic 7: Health Data: the sociology of its production and use

Key Reading

Ebeling, M.F.E. 2016. Healthcare and big data : digital specters and phantom objects ISBN: 9781137502209 (hbk.) : £66.99. Basingstoke: Palgrave. – chapter 1.  

Foster, V. and Young, A. 2012. The use of routinely collected patient data for research: a critical review. Health.. 16 (4), pp.448-463.

Kirchgaessner, S. 2016. Ethical questions raised in search for Sardinian centenarians' secrets The Guardian.. 12/08/2016

Further Reading

Brazier, M. and Lobjoit, M. 1991. Protecting the vulnerable : autonomy and consent in health care. London: Routledge.

Coopmans, C. 2006. Making mammograms mobile: Suggestions for a sociology of data mobility. Information, communication and society.. 9 (1), pp.1-19.

Ghosh, K. and Sen, K. 2015. A Conceptual Model to Understand the Factors that Drive Individual Participation in Crowdsourcing for Medical Diagnosis. In: System Sciences (HICSS), 2015 48th Hawaii International Conference on, 5-8 Jan. 2015, pp.2815-2823. - Available online: http://ieeexplore.ieee.org/document/7070156/?arnumber=7070156

Gillespie, C. 2012. The experience of risk as ‘measured vulnerability’: health screening and lay uses of numerical risk. Sociology of health and illness.. 34 (2), pp.194-207.

Hoeyer, K. and Hogle, L. F. 2014. Informed Consent: The Politics of Intent and Practice in Medical Research Ethics*. Annual review of anthropology.. 43 pp.347-362.

Keating, P. and Cambrosio, A. 2009. Who's minding the data? Data Monitoring Committees in clinical cancer trials. Sociology of health and illness.. 31 (3), pp.325-342.

Kingori, P. 2013. Experiencing everyday ethics in context: Frontline data collectors perspectives and practices of bioethics. Social science & medicine.. 98, pp.361-370.

Lupton, D. 2014. The commodification of patient opinion: the digital patient experience economy in the age of big data. Sociology of health and illness.. 36 (6), pp.856-869.

Mitchell, R. and Waldby, C. 2010. National biobanks: clinical labor, risk production, and the creation of biovalue. Science, technology, & human values.. 35 (3), pp.330-355.

Nettleton, S. and Burrows, R. 2003. E-scaped medicine? Information, reflexivity and health. Critical social policy.. 23 (2), pp.165-185.

Niezen, M.G.H., Bal, R. and De Bont, A. 2013. Reconfiguring Policy and Clinical Practice: How Databases Have Transformed the Regulation of Pharmaceutical Care? Science, technology, & human values.. 38 (1), pp.44-66.

Petersson, J. 2016. Technospatialities and telehealthcare: unfolding new spaces of visibility. Information, communication and society.. 19 (6), pp.824-842.

Rapp, R. 2015. Big data, small kids: Medico-scientific, familial and advocacy visions of human brains. BioSocieties11(3), pp.296-316.

Riedl, J. and Riedl, E. 2013. Crowdsourcing medical research. Computer.. 46 (1), pp.89-92.

Schaffer, R. et al. 2008. Producing genetic knowledge and citizenship through the Internet: mothers, pediatric genetics, and cybermedicine. Sociology of health and illness.. 30 (1), pp.145-159.

Van Dijck, J. and Poell, T. 2016. Understanding the promises and premises of online health platforms. Big data and society ISSN: 2053-9517. 3(1).

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Topic 8: Data use case studies (essay prep)

Key Reading

Cottrell, S. 2013. The study skills handbook. Basingstoke: Palgrave Macmillan. Section on Case studies (pp.272-273 in 3rd edition)

Payne, E. and Whittaker, L. 2006. Developing essential study skills. Harlow: FT Prentice Hall. Section on Case studies (pp.275-290 in 2nd edition)

Resources

University of Bradford quick scan: http://www.bradford.ac.uk/academic-skills/media/academicskillsadvice/documents/academicskillsresources/writing-essaystraditionalacademic/Infosheet-case-study.pdf

University of Hull: https://web.archive.org/web/20161020014743/http://www2.hull.ac.uk/lli/pdf/Case%20Studies.pdf

University of Southern California long thoughtful guide: http://libguides.usc.edu/writingguide/casestudy

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Topic 9: Data visualisation

Key Reading

Few, S. 2008. What ordinary people need most from information visualization today. Perceptual Edge: Visual Business Intelligence Newsletter. - Available online: http://www.perceptualedge.com/articles/visual_business_intelligence/what_people_need_from_infovis.pdf

Kennedy, H. et al. 2016. The work that visualisation conventions do. Information, communication and society.. 19 (6), pp.715-735.

Key Resources

Seeing Data website: http://seeingdata.org, especially section Developing Visualisation Literacy. This site provides details on what visualisations are, how they are made and how people engage with them.

Visualising Data website: http://visualisingdata.com. This site contains analyses and discussion of many visualisations as well as consideration of research in the field. It also is a fantastic resource should you wish to make visualisations.

Further Reading

Barnhurst, K.G. 1994. Seeing the newspaper. New York: St. Martin's Press. Chapter on ‘Critiquing charts’

Boehnert, J. 2015. The Politics of Data Visualisation. Discover Society. (23). - Available online: http://westminsterresearch.wmin.ac.uk/16947/1/index.html

Chandrasekhar, S. 1987. Truth and beauty : aesthetics and motivations in science. Chicago: University of Chicago Press.

Dick, M. 2015. Just fancy that: an analysis of infographic propaganda in The Daily Express, 1956–1959. Journalism studies.. 16 (2), pp.152-174.

D'Ignazio, C. and Klein, L.F. 2016. Feminist data visualization. Workshop on Visualization for the Digital Humanities (VIS4DH), Baltimore. IEEE. http://vis4dh.dbvis.de/papers/Feminist%20Data%20Visualization.pdf.

Friedman, V. 2008. Data visualization and infographics. Graphics, Monday Inspiration. 14, p.2008. - Available online: https://www.smashingmagazine.com/2008/01/monday-inspiration-data-visualization-and-infographics/

Friendly, M. 2008. A Brief History of Data Visualization. In: Chen, C.-h., et al. eds. Handbook of data visualization. Berlin: Springer, pp.15-56.

Galloway, A. 2011. Are some things unrepresentable? Theory, culture & society.. 28 (7-8), pp.85-102.

Glanville, R. et al. 2011. From abstract to actual: art and designer-like enquiries into data visualisation. Kybernetes. 40 (7/8), pp.1038-1044.

Heer, J. et al. 2010. A tour through the visualization zoo. New York: ACM. 53. pp.59-67. - Available online: http://queue.acm.org/detail.cfm?id=1805128

Hill, R.L. et al. 2016. Visualising junk: big data visualisations and the need for feminist data studies. Journal of Communication Inquiry. 40(4), pp.331-350.

Jones, C.A. and Galison, P. 1998. Picturing science, producing art. New York; London: Routledge.

Kennedy, H. et al. 2016. Engaging with data visualizations: users, socio-cultural factors and definitions of effectiveness. First Monday [electronic resource]. ISSN: 1396-0466. 21(11).

Kennedy, H. and Hill, R.L. 2017. The feeling of numbers: emotions in everyday engagements with data and their visualisation. Sociology. Online.

Kirk, A. 2012. Data visualization : a successful design process. Packt Publishing Ltd.

Kirk, A. 2016. Data visualisation : a handbook for data driven design. London: Sage.

Kitchin, R. et al. 2011. 1 Thinking about maps. Rethinking maps: New frontiers in cartographic theory. p1.

Kostelnick, C. 2004. Melting-pot ideology, modernist aesthetics, and the emergence of graphical conventions: The statistical atlases of the United States, 1874-1925. Defining visual rhetorics. pp.215-242.

Kostelnick, C. 2007. The Visual Rhetoric of Data Displays: The Conundrum of Clarity. IEEE Transactions on Professional Communication.. 50 (4), pp.280-294.

Latour, B. 1986. Visualization and cognition: Drawing things together. Knowledge and Society. 6, pp.1-40. - Available online: http://www.bruno-latour.fr/sites/default/files/21-DRAWING-THINGS-TOGETHER-GB.pdf

Ma, K.-L. et al. 2009. Next-generation visualization technologies: Enabling discoveries at extreme scale. SciDAC Review. 12, pp.12-21. - Available online: http://www.kennethmoreland.com/documents/SciDACSpring2009.pdf

Manovich, L. 2011. What is visualisation? Visual studies.. 26 (1), pp.36-49.

Monmonier, M.S. 1996. How to lie with maps. Chicago; London: University of Chicago Press.

Rall, K. et al. 2016. Data Visualization for Human Rights Advocacy. Journal of Human Rights Practice. 8 (2), pp.171-197.

Salvo, M.J. 2012. Visual rhetoric and big data: design of future communication. Communication Design Quarterly. 1 (1), pp.37-40. - Available online: http://dl.acm.org/citation.cfm?id=2448925

Valarakis, A. 2014. On data visualization: rhetoric and the revival of the body politic. MA thesis, University of Amsterdam. - Avaialble online: http://dare.uva.nl/document/544393

Vande Moere, A. et al. 2012. Evaluating the effect of style in information visualization. IEEE transactions on visualization and computer graphics. ISSN: 1077-2626 on. 18 (12), pp.2739-2748. - Available online: http://infoscape.org/publications/infovis12.pdf

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Topic 10: Social media data mining

Key Reading

boyd, D., & Crawford, K. 2012. Critical questions for Big Data: Provocations for a cultural, technological, and scholarly phenomenon. Information, communication and society. 15(5), pp.662-679.

Eriksson, M. 2016. Close reading big data: The Echo Nest and the production of (rotten) music metadata. First Monday [electronic resource]., 21(7-4).

Key Resource

The Digital Methods initiative at the University of Amsterdam includes a number of useful resources, including digital tools for data mining: https://wiki.digitalmethods.net/Dmi/DmiAbout

Further Reading

Andrejevic, M., Hearn, A. and Kennedy, H. 2015. Cultural studies of data mining: Introduction. European Journal of Cultural Studies ISSN: 1367-5494. 18(4-5), pp.379-394.

Baym, N. K. 2013. Data not seen: the uses and shortcomings of social media metrics. First Monday [electronic resource]., 18(10). Retrieved from http://firstmonday.org/ojs/index.php/fm/article/view/4873/3752

Brooker, P., Barnett, J., & Cribbin, T. 2016. Doing social media analytics. Big data and society, 3(2).

Cohen, R. L. 2016. Towards a quantitative feminist sociology. In L. McKie & L. Ryan (Eds.), An end to the crisis of empirical sociology? : trends and challenges in social research (pp. 117-135). Abingdon: Routledge.

Dubois, E., & Ford, H. 2015. Trace interviews: An actor-centered approach. International Journal of Communication, 9, pp.2067-2091.

Ford, H. 2016. The person in the (big) data. Retrieved from http://2plqyp1e0nbi44cllfr7pbor.wpengine.netdna-cdn.com/files/2013/01/person_in_the_big_data_report.pdf

Kennedy, H., Moss, G., Birchall, C., & Moshonas, S. 2014. Balancing the potential and problems of digital methods through action research: methodological reflections. Information, communication and society., 18(2), pp.172-186.

Kennedy, H. 2016. Post, mine, repeat : social media data mining becomes ordinary. Basingstoke: Palgrave Macmillan.

Giles, M., Helen, K., Stylianos, M., & Chris, B. 2015. Knowing your publics: The use of social media analytics in local government. Information polity: the international journal of government & democracy in the information age., 20(4), pp.287-298.

Marres, N. and Weltevrede, E. 2013. Scraping the Social? Issues in live social research. Journal of cultural economy. 6(3), pp.313-335.

Oxford Internet Institute. nd. Accessing and using big data to advance social scientific knowledge. [Online]. Available from: https://www.oii.ox.ac.uk/projects/big-data-to-advance-social-science-knowledge/.

Purohit, H., Banerjee, T., Hampton, A., Shalin, V. L., Bhandutia, N., & Sheth, A. 2016. Gender-based violence in 140 characters or fewer: A #BigData case study of Twitter. First Monday [electronic resource]., 21(1-4).

Rogers, R. 2013. Digital methods. Cambridge, MA: MIT Press.

Rogers, R. 2015. Digital methods for web research. In R. Scott & S. Kosslyn (Eds.), Emerging Trends in the Social and Behavioral Sciences: John Wiley & Sons. - Available online: http://www.govcom.org/publications/full_list/etrds0076.pdf

Ruppert, E. 2013. Rethinking empirical social sciences. Dialogues in Human Geography. 3 (3), pp.268-273.

van Dijck, J. 2013. The culture of connectivity : a critical history of social media. Oxford: Oxford University Press.

Vis, F. 2013. A critical reflection on Big Data: considering APIs, researchers and tools as data makers. First Monday [electronic resource]. ISSN: 1396-0466. 18(10).

Welles, B. F. 2014. On minorities and outliers: The case for making Big Data small. Big data and society, 1(1).

This list was last updated on 19/09/2017