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@Berk, R. (2016) Statistical learning from a regression perspective, chapter 1, 3 and 5. Springer (164)
@Berk, Richard A., Susan B. Sorenson, Geoffrey Barnes (2016) “Forecasting Domestic Violence: A Machine Learning Approach to Help Inform Arraignment Decisions”, Journal of empirical legal studies, 13(1): 94-115 http://onlinelibrary.wiley.com/doi/10.1111/jels.12098/abstract (21 sider)
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@Brandsar, Torgeir, and Torkild Hovde Lyngstad. (2014) "Transaction data from social media: An introduction with an example on networks of members of the Norwegian parliament." TIDSSKRIFT FOR SAMFUNNSFORSKNING 55.1: 90-105. (15 sider)
@Degli Esposti, S. (2014). When big data meets dataveillance: The hidden side of analytics. Surveillance & Society 12(2):209-225 (16 sider)
@van Dijck, José. (2014). Datafication, dataism and dataveillance: Big Data between scientific paradigm and ideology. Surveillance & Society 12(2): 197-208. (11 sider)
@Frade, Carlos (2016) “Social Theory and the Politics of Big Data and Method”, Sociology, 50(5): 863-877, http://journals.sagepub.com/doi/abs/10.1177/0038038515614186 (14 sider)
@Frey and Osborne (2017) “The future of employment: How susceptible are jobs to computerisation?” Technological Forecasting & Social Change 114 (2017) 254–280 (26 sider)
@Gandy, O.H. (2017). Surveillance and the Formation of Public Policy. Surveillance & Society 15(1): 158-171. (13 sider)
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@Gunderson, Ryan (2016) “The sociology of technology before the turn to technology”, Technology in society, 47:40-48
@Halford, S., Savage, M. (2017), Speaking Sociologically with Big Data: Symphonic Social Science and the Future for Big Data Research. Sociology 0, 0038038517698639.
@Kosinski, Michal, and Yilun Wang. (2017). “Deep Neural Networks Are More Accurate Than Humans at Detecting Sexual Orientation from Facial Images.”. PsyArXiv. September 16. psyarxiv.com/hv28a. (47 sider)
@Kramer, Adam D. I., Jamie E. Guillory, and Jeffrey T. Hancock (2014), “Experimental evidence of massive-scale emotional contagion through social networks” PNAS 2014 111 (24) 8788-8790; published ahead of print June 2, 2014, doi:10.1073/pnas.1320040111 (3 sider)
@Leigh, J., Dunnett, S. & Jackson, L. Ann (2017). “Predictive police patrolling to target hotspots and cover response demand”, Operational Research, doi:10.1007/s10479-017-2528-x (16 sider)
@Lysne et al (2016) Digitalt grenseforsvar (DGF), Lysne II utvalget, https://www.regjeringen.no/globalassets/departementene/fd/dokumenter/lysne-ii-utvalgets-rapport-2016.pdf (71 sider)
@McFarland, D.A., Lewis, K. & Goldberg, A. (2016) “Sociology in the Era of Big Data: The Ascent of Forensic Social Science”, American Sociologist, 47(12): 12-35. doi:10.1007/s12108-015-9291-8 (20 sider)
Schneier, Bruce (2015) “Data as a by-product of computing”, i: Data and Goliath, New York: W.W. Norton & Company, (7 sider) gjøres tilgjengelig på fronter
@Srnicek, N. (2017), The challenges of platform capitalism: Understanding the logic of a new business model. Juncture, 23: 254–257. doi:10.1111/newe.12023
@Siegel, Eric (2011) Uplift modeling: Predictive analytics can’t optimize marketing decisions without it. The Prediction Impact white paper, Pitney Bowes: http://www.predictiveanalyticsworld.com/pdf/YTW03080USEN/Uplift-Modeling-Optimizes-Marketing-Decisions-White-Paper.pdf (24 sider)
BOK: Susskind, Richad & Daniel Susskind (2015) The future of the professions. How technology will transform the work of human experts, UK: Oxford University Press (Introduction, Kapitlene 1, 5, 6, 7)
@Zwitter, A. (2014). Big Data ethics. Big Data & Society 1, 2053951714559253. (6 sider)
Anbefalt litteratur:
@Atkinson, R.D. & Wu, John (2017) Fals alarmism: Tehcnological disruption and the U.S. labor market, 1850-2015, Information technology & innovation foundation, @work series May 2017, URL: https://itif.org/publications/2017/05/08/false-alarmism-technological-disruption-and-us-labor-market-1850-2015
Øvrige kapitler i Sussking & Susskind (2015), Schneier (2015), og Berk (2016)