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Big Data e Valutazione: una relazione ancora da costruire
Titolo Rivista: RIV Rassegna Italiana di Valutazione 
Autori/Curatori: Francesco Mazzeo Rinaldi 
Anno di pubblicazione:  2017 Fascicolo: 68 Lingua: Italiano 
Numero pagine:  19 P. 7-25 Dimensione file:  415 KB
DOI:  10.3280/RIV2017-068002
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Recent years have witnessed a tremendous growth in globally generated data as well as in the fast evolution of technologies that allows, in real time, to capture, analyse, and exploit huge data repositories. As data sizes grows, so does the general agreement that data is highly valuable. The automatic extraction of information, together with pioneering data mining and predictive analytics techniques, represents an effective and competitive opportunity, particularly to support decision making processes to answer various research and evaluation questions. In this context Big Data (BD) and the Computational Social Science (CSS) approaches, are expected to challenge the ways social scientist, analysts, and evaluators have worked so far. Big Data are today generally utilized by private business while they remain deeply underutilized in public policy-making sector. Its potential has probably not yet been fully understood. Although significant economic incentives made private businesses move first, there is no reason to hold proper usage of Big Data in the public sector. In evaluation research, BD is even more under-utilized, even when the evaluated interventions could be closely monitored in real-time, this is rarely done. At the present time, there is no much scientific and professional debate on how to integrate Big Data within the evaluation research field. Hence, the main aim of this special issue is to improve knowledge on applicability of BD techniques in the evaluation research for supporting decision-making processes.
Keywords: Big Data; Evaluation Research; Computational Social Science.

  1. Abbagnano N. (1961) Dizionario di Filosofia. Torino, UTET.
  2. Agnoli S., Parra Saiani P. (a cura) Sulle Tracce dei Big Data. Questioni di Metodo e Percorsi di Ricerca. Sociologia e Ricerca Sociale 109, FrancoAngeli, Milano.
  3. Agodi M.C. (a cura) (2010) Tracce nella Rete: dai consumi ai reati di mafia. Quaderni di Sociologia 54(3).
  4. Anderson C. (2008) The end of theory: The data deluge makes the scientific method obsolete, Wired. 23 June 2008. -- http://www.wired.com/science/discoveries/magazine/16-07/pb_theory.
  5. Bamberger, M (2017) Integrating big data into the monitoring and evaluation of development programs. UN Global Pulse with support from the Rockefeller Foundation.
  6. Bollier D. (2010) The Promise and Peril of Big Data. The Aspen Institute.
  7. Botsman R. (2017) Big data meets Big Brother as China moves to rate its citizens Wired, 21 October 2017. -- http://www.wired.co.uk/article/chinese-government-social-credit-score-privacy-invasion.
  8. Brayne S. (2017) Big Data Surveillance: The Case of Policing. American Sociological Review 82(5) 977-1008
  9. Couldry N. (2014) Inaugural: A Necessary Disenchantment: Myth, Agency and Injustice in a Digital World. The Sociological Review 62(4) 880-897.
  10. Crompton R. (2008) 40 years of sociology: Some comments. Sociology 42(6): 1218–1227.
  11. Daboll P. (2013) 5 Reasons Why Big Data Will Crush Big Research, Forbes. -- http://www.forbes.com/sites/onmarketing/2013/12/03/5-reasons-why-big-data-will-crushbig-research/
  12. De Leonardis O., Neresini F. (a cura) (2014) Il potere dei grandi numeri. Rassegna Italiana di Sociologia LVI 3-4. Il Mulino.
  13. Einav L., Levin J.D. (2013) The data revolution and economic analysis, NBER Working Paper Series No. 19035. -- http://www.nber.org/papers/w19035.
  14. Frade C. (2016) Social theory and the politics of big data and method. Sociology 50(5) 863–877.
  15. Giuffrida G., Gozzo S., Mazzeo Rinaldi F, Tomaselli V. (2017) Big Data and Network Analysis: a Promising Integration for Decision-Making, in (eds.) Lauro N.C., Amaturo E., Grassia M.G., Aragona B., Marino M., Data Science and Social Research - Epistemology, Methods, Technology and Applications’ Studies. Springer. ISBN: 978-3-319-55477-8.
  16. Giuffrida G., Mazzeo Rinaldi F, Zarba C. (2016) Big data e news online: possibilità e limiti per la ricerca sociale, in (a cura di) Agnoli S., Parra Saiani P., Sulle Tracce dei Big Data. Questioni di Metodo e Percorsi di Ricerca. Sociologia e Ricerca Sociale, n. 109, pp.159-173 FrancoAngeli, Milano., 10.3280/SR2016-109013DOI: 10.3280/SR2016-109013
  17. Golder S.A., Macy M.W. (2014) Digital Footprints: Opportunities and Challenges for Online Social Research. Annual Review of Sociology 40(1) 129-152.
  18. Goldthorpe J. (2016) Sociology as a Population Science. Cambridge: Cambridge University Press. Graham M. (2012) Big data and the end of theory. The Guardian. -- http://www.guardian.co.uk/news/datablog/2012/mar/09/big-data-theory.
  19. Halford S., Savage M. (2017) Speaking Sociologically with Big Data: Symphonic Social Science and the Future for Big Data Research. Sociology 51(6) 1-17., 10.1177/0038038517698639DOI: 10.1177/0038038517698639
  20. Høljund, S., Olejniczak, K., Petersson, G., & Rok, J. (2017) The Current Use of Big Data in Evaluation. In G. Petersson & J. Breul (eds.), Cyber Society, Big Data and Evaluation. New Brunswick, NJ: Transaction Publisher.
  21. Kitchin R. (2014) Big data, new epistemologies and paradigm shifts. Big Data & Society, 1(1) 1-12., 10.1177/2053951714528481DOI: 10.1177/2053951714528481
  22. Lagoze C. (2014) Big Data, data integrity, and the fracturing of the control zone. Big Data & Society 1(2) 1-11., 10.1177/2053951714558281DOI: 10.1177/2053951714558281
  23. Laney D. (2001) 3D data management: Controlling data volume, variety and velocity, Technical report, META Group, -- testo disponibile al sito: http://blogs.gartner.com/douglaney/files/2012/01/ad949-3D-Data-Management-Controlling-Data-Volume-Velocity-and-Variety.pdf.
  24. Lazer D., Radford J. (2017) Data ex Machina: Introduction to Big Data. Annual Review of Sociology 43(1) 19-39. Lazer, D., R Kennedy., King G., Vespignani A. (2014) The Parable of Google Flu: Traps in Big Data Analysis, Science, 343(6176) 1203–1205.
  25. Ma A. (2018) China ranks citizens with a social credit system – here’s what you can do wrong and how you can be punished. Business Insider, Independent, published on Tuesday 10 April 2018. -- https://www.independent.co.uk/life-style/gadgets-and-tech/china-social-creditsystem-punishments-rewards-explained-a8297486.html.
  26. Marres N., Gerlitz C. (2016) Interface methods: Renegotiating the relations between digital social research, STS and the sociology of innovation. Sociological Review 64 21–46.
  27. Mayer-Schönberger V., Cukier K. (2013) Big data: A revolution that will transform how we live, work, and think, New York, NY, Houghton Mifflin Harcourt.
  28. Mazzeo Rinaldi F, Giuffrida G, Negrete T. (2017) Real-time monitoring and evaluation – Emerging news as predictive process using Big Data based approach, in: (eds): Petersson G., Breul J.D., Cyber Society, Big Data and Evaluation. vol. 24, pp. 191-214, New Brunswick, NJ: Transaction Publishers.
  29. McKenzie Finucane M., Martinez I., Cody S. (2017) What Works for Whom? A Bayesian Approach to Channeling Big Data Streams for Public Program Evaluation. American Journal of Evaluation 39(1) 109-122.
  30. Petersson G., Breul J. (eds.) (2017) Cyber Society, Big Data and Evaluation. New Brunswick, NJ: Transaction Publishers.
  31. Raftree L. (2015) Big data in development evaluation. -- https://lindaraftree.com/2015/11/23/big-datain-development-evaluation/.
  32. Savage M., Burrows R. (2007) The coming crisis of empirical sociology. Sociology 41(5) 885–899., 10.1177/0038038507080443DOI: 10.1177/0038038507080443
  33. Savage M., Burrows R. (2009) Some further reflections on the coming crisis of empirical sociology. Sociology 43(4) 762-772., 10.1177/0038038509105420DOI: 10.1177/0038038509105420
  34. Savage M., Burrows R. (2014) After the crisis? Big Data and the methodological challenges of empirical sociology. Big Data & Society, April–June 2014 1–6. DOI 10.1177/2053951714540280.
  35. Siegel E. (2013) Predictive Analytics. Hoboke, N.J, Wiley.
  36. Stephens-Davidowitz S. (2017). Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are. New York: Harper Collins Publishers.
  37. Swan M., (2013) The Quantified Self: Fundamental Disruption in Big Data Science and Biological Discovery. Big Data. 1(2) 85-99.
  38. Taylor L., Schroeder R., Meyer E. (2014) Emerging practices and perspectives on Big Data analysis in economics: bigger and better or more of the same? Big Data & Society 1
  39. Vitak J., Zube P., Smock A., Carr C.T., Ellison N., Lampe C. (2011) It’s Complicated: Facebook Users’ Political Participation in the 2008 Election, Cyber-psychology, Behavior, and Social Networking 14(3) 107-114.
  40. Williams M., Burnap P., Sloan L. (2017) Crime sensing with big data: The affordances and limitations of using open-source communications to estimate crime patterns. British Journal of Criminology 57(2) 320–340.
  41. Wolf G. (2010) The Data Driven Life. New York Times, published on 28 April 2010. -- https://www.nytimes.com/2010/05/02/magazine/02self-measurement-t.html.
  42. Zafarani R., Abbasi M.A., Liu H. (2014) Social Media Mining. An Introduction. Cambridge University Press.

Francesco Mazzeo Rinaldi, in "RIV Rassegna Italiana di Valutazione" 68/2017, pp. 7-25, DOI:10.3280/RIV2017-068002

   

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