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Types of Big Data and designs of evaluation research
Journal Title: RIV Rassegna Italiana di Valutazione 
Author/s: Biagio Aragona 
Year:  2017 Issue: 68 Language: Italian 
Pages:  15 Pg. 48-62 FullText PDF:  376 KB
DOI:  10.3280/RIV2017-068004
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Keywords: Big Data Research; Research Design; Evaluation Research; Evaluation Objective; Big Data Typology.

  1. Amaturo E, Punziano G, (2015) I mixed methods nella ricerca sociale, Roma: Carocci
  2. Aragona, B. (2018). Una nuova cultura del dato. Sociologia e ricerca sociale, 87(3): 151-173,, 10.3280/SR2018-087004DOI: 10.3280/SR2018-087004
  3. Aragona, B. (2016). Big Data or data that are getting bigger?. Sociologia e ricerca sociale, 109(3): 42-53,, 10.3280/SR2016-109005;DOI: 10.3280/SR2016-109005;
  4. Aragona B., Zindato D. (2016), Counting people in the data revolution era: challenges and opportunities for population censuses, International Review of Sociology, 26(3), 367-385,, 10.1080/03906701.2016.124492DOI: 10.1080/03906701.2016.124492
  5. Bezzi, C.. (2001) Il disegno della ricerca valutativa, Milano: Franco Angeli.
  6. Boccia Artieri, G. (2015). Gli effetti sociali del web. Forme della comunicazione e metodologie della ricerca online. Milano: FrancoAngeli.
  7. Botta, F., Moat, H. S., and Preis, T. (2015). Quantifying crowd size with mobile phone and Twitter data. Royal Society open science, 2(5): 150-162.
  8. Boyd, D., Crawford, K. (2012). Critical questions for Big Data. Information, Communication and Society, 15(5): 662–679.
  9. Clubb, J.M., Scheuch, E.K. (1980), Historical social research: the use of historical and processproduced data. Stuttgart: Klett-Cotta;
  10. Conte, R. (2016), Big Data: un’opportunità per le scienze sociali?, Sociologia e Ricerca Sociale, 109(3), 18-27.
  11. Davies, T. (2013). Open data barometer: 2013 global report. World Wide Web Foundation and Open Data Institute.
  12. Diesner, J. (2015). Small decisions with big impact on data analytics. Big Data & Society, 2(2), 24-32,, 10.1177/20253951715617185DOI: 10.1177/20253951715617185
  13. Elias P (2012) Big data and the social sciences: a perspective from the ESRC, presentation at the conference Shaping society.
  14. Gray, E., Jennings, W., Farrall, S., and Hay, C. (2015). Small Big Data: Using multiple data-sets to explore unfolding social and economic change. Big Data & Society, 2(1),
  15. Höchtl, J. Parycek, P., and Schöllhammer, R. (2016). Big Data in the policy cycle: Policy decision making in the digital era, Journal of Organizational Computing and Electronic Commerce, 26:1-2, 147-169,, 10.1080/10919392.2015.112518DOI: 10.1080/10919392.2015.112518
  16. King G., Pan J., Roberts M. E. (2013). How censorship in China allows government criticism but silences collective expression, American Political Review, 107(2), 2013, 326-43.
  17. Kitchin, R. (2014) The Data Revolution: Big Data, Open Data, Data Infrastructures and Their Consequences. London: Sage.
  18. Kourtit, K., Nijkamp, P., and Arribas-Bel, D. (2012). Smart cities perspective – a comparative European study by means of self-organizing maps, Innovation, 25(2): 229-46
  19. Lettieri, N. 2016, Computational Social Science, the Evolution of Policy Design and Rule Making in Smart Societies, Future internet, 8, 19, 1-17.
  20. Lorentzen, P. (2014). China’s strategic censorship, American Journal of Political Science 58(2): 402–414.
  21. Lyon, D. (2007). Surveillance Studies: An overview, Cambridge: Polity.
  22. Marradi A (2006) Metodologia delle scienze sociali. Bologna: Il Mulino.
  23. Manning, C.D., Raghavan, P., and Schütze, H. (2008). Introduction to information retrieval. Cambridge: Cambridge University Press.
  24. Martinotti, G. (1988) Metropolitan areas in Italy 1961-1981: A statistical exploration into criteria for definition. working paper of the Second international conference on policies strategies and projects for metropolitan areas;
  25. Mattern, S. (2013) Methodolatry and the art of measure: the new wave of urban data science. Design Observer: Places, 5 November -- http://designobserver.com/places/feature/0/38174.
  26. Milan, S. (2017). Data activism as the new frontier of media activism, in Media Activism in the Digital Age, G. Yang and V. Pickard (eds), London: Routledge.
  27. OECD, (2015). Exploring Data Driven Innovation as a New Source of Growth mapping the policy issues raised by “Big Data”. OECD. Sagiroglu, S. and Sinanc, D. (2013). Big Data: A review. In Collaboration Technologies and Systems (CTS), 2013 International Conference CTS 20-24 May San Diego. IEEE: (pp. 42-47).
  28. Savage, M., Burrows R (2007) The coming crisis of empirical sociology. Sociology 41(5): 885–899.
  29. Savage, M., Burrows, R. (2014). After the Crisis? Big Data and the Methodological Challenges of Empirical Sociology. Big Data and Society, April-June, pp. 1-6,, 10.1177/2053951714540280DOI: 10.1177/2053951714540280
  30. Stame, N. (1998). L'esperienza della valutazione. Roma: Seam.
  31. Sen, A. (1982). Choice, welfare and measurement. Cambridge, MA: Harvard University Press;
  32. Supiot, A. (2016) La Gouvernance par les nombres, Paris: Fayard.
  33. Sundgren, B. (1995). Guidelines for the Modelling of Statistical Data and Metadata. New York: U.N.
  34. Taylor, L, Schroeder, R. and Meyer, E. (2014). Emerging practices and perspectives on Big Data analysis in economics: Bigger and better or more of the same?. Big Data and Society, 1(2): 7-16., 10.1177/20253951715602908DOI: 10.1177/20253951715602908
  35. Vemuganti, G. (2013) Metadata Management in Big Data. Infosys Labs Briefings, 11(1), pp.16-20; Webb, E.J. Campbell, D.T., Schwartz R.D. (1966). Unobtrusive Methods: Non-reactive Research in the Social Sciences. Chicago: Rand McNally.

Biagio Aragona, in "RIV Rassegna Italiana di Valutazione" 68/2017, pp. 48-62, DOI:10.3280/RIV2017-068004

   

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