Trust, Disconnection, Minimizing risk and Apathy
A Compass of Coping Tactics in Datafied Everyday Lives
This paper investigates how audiences are coping with digital platforms in their everyday lives. Empirically grounded in focus groups carried out in Denmark with a total of 34 participants of different ages and educational backgrounds, we present the results of an analysis of audiences’ coping tactics in relation to tracking data, collecting data and mining data.
Based on the analysis, we find four overall tactics: coping by absence, coping by trust, coping by minimizing risk and coping by apathy. We argue that these different coping tactics are employed differently depending on the context of the digital routines, the data collected (sensitive vs. non-sensitive data), and the dependence of the platform (private vs. public, national vs. international platforms and apps). These contextual factors are presented in an analytical model—a coping compass—for studying individual users’ coping tactics in their datafied everyday lives.
Andrejevic, M. (2014). The big data divide. International Journal of Communication. 11, 1673-1689. https://doi.org/1932–8036/20140005
Barbour, R., & Kitzinger, J. (1999). Introduction: The challenge and promise of focus groups. In J. Kitzinger & R.S. Barbour (Eds.), Developing focus group research (pp. 1–20). London: SAGE. https://doi.org/10.4135/9781849208857.n1
Bloor, M., Frankland, J., Thomas, M., & Robson, K. (2012). Focus groups in social research. London: SAGE. https://doi.org/10.4135/9781849209175
Bolin, G., & Andersson Schwarz, J. (2015). Heuristics of the algorithm: Big data, user interpretation and institutional translation. Big Data & Society, December 2(2), 1–12. https://doi.org/10.1177/2053951715608406
Bottis, M., & Bouchagiar, G. (2018). Personal data v. big data in the EU: Control lost, discrimination found. Open Journal of Philosophy, 8, 192–205. https://doi.org/10.4236/ojpp.2018.83014
Cate, F.H., & Mayer-Schonberger, V. (2013). Notice and consent in a world of big data. International Data Privacy Law, 3(2), 67-73. International Data Privacy Law. https://doi.org/10.1093/idpl/ipt005
Couldry, N., & Mejias, U.A. (2018). Data Colonialism: Rethinking Big Data’s Relation to the Contemporary Subject. Television and New Media. 20(4), 336-349. https://doi.org/10.1177/1527476418796632
Crawford, K., & Schultz, J. (2014). Big data and due process: Toward a framework to redress predictive privacy harms. Boston College Law Review, 55(93), 93-128.
de Certeau, M. (1988). The practice of everyday life: ‘making do’: Uses and tactics. In G.M. Spiegel (Ed.), Practicing history: New directions in historical writing after the linguistic turn (pp. 217-227). New York: Routledge. https://doi.org/10.4324/9780203335697
Dencik, L., & Cable, J. (2017). The advent of surveillance realism: Public opinion and activist responses to the Snowden leaks. International Journal of Communication, 11, 763–781.
Dencik, L., Hintz, A., & Carey, Z. (2018). Prediction, pre-emption and limits to dissent: Social media and big data uses for policing protests in the United Kingdom. New Media and Society, 20(4), 1433 –1450. https://doi.org/10.1177/1461444817697722
Draper, N.A., & Turow, J. (2019). The corporate cultivation of digital resignation. New Media and Society, 21(8), 1824-1839. https://doi.org/10.1177/1461444819833331
Frederiksen, M. (2016). Divided uncertainty: A phenomenology of trust, risk and confidence. In S. Jagd & F.L (Eds.), Trust, Organizations and Social Interaction: Studying Trust as Process within and between Organizations (pp. 43-67). https://doi.org/10.4337/9781783476206.00011
Gerber, N., Gerber, P., & Volkamer, M. (2018). Explaining the privacy paradox: A systematic review of literature investigating privacy attitude and behavior. Computers and Security, 77, 226-261. https://doi.org/10.1016/j.cose.2018.04.002
Gray, J., Gerlitz, C., & Bounegru, L. (2018). Data infrastructure literacy. Big Data and Society 5 (2). https://doi.org/10.1177/2053951718786316
Hargittai, E., & Marwick, A. (2016). ‘What can I really do?’ Explaining the privacy paradox with online apathy. International Journal of Communication, 10(2016), 3737-3757. https://doi.org/10.5167/uzh-148157
Kennedy, H. (2018). Living with data: Aligning data studies and data activism through a focus on everyday experiences of datafication. Krisis: Journal for Contemporary Philosophy, 1.
Kennedy, H., Elgesem, D., & Miguel, C. (2017). On fairness: User perspectives on social media data mining. Convergence 23 (3). https://doi.org/10.1177/1354856515592507
Kitzinger, J. (1994). The methodology of focus groups: The importance of interaction between research participants. Sociology of Health & Illness 16(1). https://doi.org/10.1111/1467-9566.ep11347023
Latour, B., & Johnson, J. (1998). Mixing humans and nonhumans together: The sociology of a door-closer. Social Problems, 35(3), 298–310. https://doi.org/10.1525/sp.1988.35.3.03a00070
Mayer-Schönberger, V., & Cukier, K. (2013). Big Data: A Revolution That Will Transform How We Live, Work and Think. New York: Houghton Miffl in Harcourt. https://doi.org/10.3359/oz1314047
Millington, B., & Millington, R. (2015). ‘The datafication of everything’: Toward a sociology of sport and big data. Sociology of Sport Journal 32(2). https://doi.org/10.1123/ssj.2014-0069
Newman, N., Levy, D.A.L., & Nielsen, R.K. (2018). Reuters Institute Digital News Report 2018. University of Oxford. https://doi.org/10.1017/CBO9781107415324.004
OECD. (2019). OECD Economic Surveys - Denmark.
Pangrazio, L., & Selwyn, N. (2018). ‘Personal data literacies’: A critical literacies approach to enhancing understandings of personal digital data. New Media & Society 21(2). https://doi.org/10.1177/1461444818799523
Picone, I., Kleut, J., Pavlíčková, T., Romic, B., Møller Hartley, J., & De Ridder, S. (2019). Small acts of engagement: Reconnecting productive audience practices with everyday agency. New Media and Society 21(9). https://doi.org/10.1177/1461444819837569
Pink, S., Lanzeni, D., & Horst, H. (2018). Data anxieties: Finding trust in everyday digital mess. Big Data & Society, January 5(1), 1–14. https://doi.org/10.1177/2053951718756685
Ruckenstein, M., & Schüll, N.D. (2017). The datafication of health. Annual Review of Anthropology, 46(1), 261-278. https://doi.org/10.1146/annurev-anthro-102116-041244
Smith, G.J.D., & O’Malley, P. (2017). Driving politics: Data-driven governance and resistance. British Journal of Criminology 57(2), 275–298. https://doi.org/10.1093/bjc/azw075
Sumartojo, S., Pink, S., Lupton, D., & LaBond, C.H. (2016). The affective intensities of datafied space. Emotion, Space and Society, 21, 33-40.. https://doi.org/10.1016/j.emospa.2016.10.004
van Dijck, J. (2014). Datafication, dataism and dataveillance: Big data between scientific paradigm and ideology. Surveillance and Society, 12(2), 197–208. https://doi.org/10.24908/ss.v12i2.4776
Willson, M. (2017). Algorithms (and the) everyday. Information Communication and Society 20(1), 137-150. https://doi.org/10.1080/1369118X.2016.1200645
Young, A.L., & Quan-Haase, A. (2013). Privacy protection strategies on Facebook: The Internet privacy paradox revisited. Information Communication and Society. 16(4), 479-500. https://doi.org/10.1080/1369118X.2013.777757
Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. New York: PublicAffairs. https://doi.org/10.4000/qds.3723
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