Clicca qui per scaricare

La profondità dei big data. Datacentrismo, ragnatele di significati digitali e cultura algoritmica
Autori/Curatori: Antonio Di Stefano 
Anno di pubblicazione:  2016 Fascicolo: 109 Lingua: Italiano 
Numero pagine:  16 P. 54-69 Dimensione file:  97 KB
DOI:  10.3280/SR2016-109006
Il DOI è il codice a barre della proprietà intellettuale: per saperne di più:  clicca qui   qui 

The main objective of this paper is to describe and analyze the high cultural density and ideological character of the Big Data phenomenon. The technical nature of computational models and the affirmative logic of algorithmic culture conceal the functioning of the mechanisms, simultaneously symbolic and ideological, that contribute to structuring Big Data. As data, it represents the result of an intricate process of construction, imagination, and interpretation. On the other hand, the role played by powerful technological corporations and by a specific form of neoliberal state highlights only the exchange value of Big Data, the production of which is aimed to fulfil commercial and surveillance needs.

  1. C. Anderson (2008), «The End of Theory: The Data Deluge makes the Scientific Method Obsolete », Wired, June 23,
  2. Z. Bauman, D. Lyon (2013), Liquid Surveillance: A Conversation, Cambridge, Polity Press. D. Beer (2009), «Power through the Algorithm? Participatory Web Cultures and the Technological Unconscious», New Media & Society, 11, pp. 985-1002,, 10.1177/1461444809336551DOI: 10.1177/1461444809336551
  3. D. Berry (2011), «The Computational Turn: Thinking about the Digital Humanities», Culture Machine, 12,
  4. d. boyd, K. Crawford (2012), «Critical Questions for Big Data: Provocations for a Cultural, Technological, and Scholarly Phenomenon», Information, Communication & Society, XV, 5, pp. 662-79,, 10.1080/1369118X.2012.678878DOI: 10.1080/1369118X.2012.678878
  5. D. Brooks (2013), «What Data can’t do», New York Times, February 18. R. Burrows, M. Savage (2014), «After the Crisis? Big Data and the Methodological Challenges of Empirical Sociology», Big Data and Society, 1, pp. 1-6,, 10.1177/2053951714540280DOI: 10.1177/2053951714540280
  6. J. Cheney-Lippold (2011), «A New Algorithmic Identity: Soft Biopolitics and the Modulation of Control», Theory, Culture & Society, XXVIII, 6, pp. 164-81,, 10.1177/0263276411424420DOI: 10.1177/0263276411424420
  7. N. Couldry, A. Powell (2014), «Big Data from the bottom up», Big Data and Society, 1, pp. 1-5,, 10.1177/2053951714539277DOI: 10.1177/2053951714539277
  8. K. Crawford (2013), «The Hidden Biases in Big Data», Harvard Business Review,
  9. P. Du Gay, M. Pryke (2002), Cultural Economy: Cultural Analysis and Commercial Life, London, Sage.
  10. N. Ellison, R. Heino, J. Gibbs (2006), «Managing Impressions Online: Self-Presentation Processes in the Online Dating Environment», Journal of Computer-Mediated Communication, XI, 2, pp. 415-41,, 10.1111/j.1083-6101.2006.00020.xDOI: 10.1111/j.1083-6101.2006.00020.x
  11. H. Ford (2014), «Big Data and Small: Collaborations between Ethnographers and Data Scientists », Big Data & Society, 1, pp. 1-3,, 10.1177/2053951714544337DOI: 10.1177/2053951714544337
  12. C. Geertz (1973), The Interpretation of Cultures, New York, Basic Books; tr. it., Interpretazioni di culture, Bologna, il Mulino, 1998.
  13. L. Gitelman (ed.) (2013), «Raw Data» is an Oxymoron, Cambridge, The Mit Press.
  14. L. Gitelman, V. Jackson (2013), Introduction, in L. Gitelman (ed.), «Raw Data» is an Oxymoron, Cambridge, The Mit Press.
  15. B. Hallinan, T. Striphas (2016), «Recommended for you: The Netflix Prize and the Production of Algorithmic Culture», New Media & Society, 18 (1), pp. 117-37,, 10.1177/1461444814538646DOI: 10.1177/1461444814538646
  16. M. Hardt, A. Negri (2012), Questo non è un manifesto, Milano, Feltrinelli.
  17. H. Kennedy, T. Poell, J. van Dijck (2015), «Data and Agency», Big Data & Society, 1, pp. 1-7,, 10.1177/2053951715621569DOI: 10.1177/2053951715621569
  18. R. Kitchin (2014a), «Big Data and Human Geography: Opportunities, Challenges and Risks», Dialogues in Human Geography, III, 3, pp. 262-7,, 10.1177/2043820613513388DOI: 10.1177/2043820613513388
  19. R. Kitchin (2014b), «Big Data, New Epistemologies and Paradigm Shifts», Big Data & Society, 1, pp. 1-12,, 10.1177/2053951714528481DOI: 10.1177/2053951714528481
  20. R. Lake (2013), A Curriculum of Imagination in an Era of Standardization: An Imaginative Dialogue with Maxine Greene and Paulo Freire, Charlotte, Information Age Pub.
  21. S. Leonelli (2014), «What Difference does Quantity make? On the Epistemology of Big Data in Biology», Big Data & Society, 1, pp. 1-11,, 10.1177/2053951714534395DOI: 10.1177/2053951714534395
  22. D. Lyon (2014), «Surveillance, Snowden, and Big Data: Capacities, Consequences, Critique», Big Data & Society, 1, pp. 1-13,, 10.1177/2053951714541861DOI: 10.1177/2053951714541861
  23. L. Manovich (2011), Trending: The Promises and the Challenges of Big Social Data, in M.K. Gold (ed.), Debates in the Digital Humanities, Minneapolis, The University of Minnesota Press.
  24. A.E. Marwick, d. boyd (2011), «I Tweet Honestly, I Tweet Passionately: Twitter Users, Context Collapse, and the Imagined Audience», New Media & Society, XIII, 1, pp. 114-33,, 10.1177/1461444810365313DOI: 10.1177/1461444810365313
  25. E. Morozov (2013), To save Everything click here. Technology, Solutionism and the Urge to fix Problems that don’t exist, New York, Allen Lane; tr. it., Internet non salverà il mondo, Milano, Mondadori, 2014.
  26. Z. Papacharissi (2015a), «The Unbearable Lightness of Information and the Impossible Gravitas of Knowledge: Big Data and the Makings of a Digital Orality», Media, Culture & Society, XXXVII, 7, pp. 1095-100,, 10.1177/0163443715594103DOI: 10.1177/0163443715594103
  27. Z. Papacharissi (2015b), Affective Publics: Sentiment, Technology, and Politics, Oxford, Oxford University Press P. Park, M. Macy (2015), «The Paradox of Active Users», Big Data & Society, 1, pp. 1-4,, 10.1177/2053951715606164DOI: 10.1177/2053951715606164
  28. M. Pasquinelli (2009), Google’s PageRank Algorithm: A Diagram of the Cognitive Capitalism and the Rentier of the Common Intellect, in K. Becker, F. Stalder (ed.), Deep Search: The Politics of Search Beyond Google, London: Transaction Publishers.
  29. D.V. Shah, J.N. Cappella, W. Russell Neuman (2015), «Big Data, Digital Media, and Computational Social Science: Possibilities and Perils», The Annals of the American Academy of Political and Social Science, 659, pp. 6-13,, 10.1177/0002716215572084DOI: 10.1177/0002716215572084
  30. T. Terranova (2014), Red Stack Attack! Algorithms, Capital and the Automation of the Common, in R. Mackay, A. Avanessian (ed.), #Accelerate: The Accelerationist Reader, Falmouth, Urbanomic.
  31. A. Zwitter (2014), «Big Data ethics», Big Data & Society, 1, pp. 1-6,, 10.1177/2053951714559253DOI: 10.1177/2053951714559253

Antonio Di Stefano, in "SOCIOLOGIA E RICERCA SOCIALE " 109/2016, pp. 54-69, DOI:10.3280/SR2016-109006


FrancoAngeli è membro della Publishers International Linking Association associazione indipendente e no profit per facilitare l'accesso degli studiosi ai contenuti digitali nelle pubblicazioni professionali e scientifiche