Davide Bennato, Il computer come macroscopio. Big data e approccio computazionale per comprendere i cambiamenti sociali e culturali, Angeli, 2015
10.6092/issn.2038-3460/17350
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2038-3460
17350
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Tommaso Venturini
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Tecnoscienza – Italian Journal of Science & Technology Studies
Davide Bennato, The computer as a macroscope. Big data and computational approaches to understand social and cultural changes, Angeli, 2015
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https://tecnoscienza.unibo.it/
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Book Reviews
2017-07-20
2023-06-22
2017-07-20
2023-08-21
151-153
TS
Tommaso Venturini
2017/07/20
10.6092/issn.2038-3460/17350
151
Université de Lyon, Inria, ENS Lyon, CNRS, UCB Lyon 1
2038-3460
1
en
153
Davide Bennato, The computer as a macroscope. Big data and computational approaches to understand social and cultural changes, Angeli, 2015
https://tecnoscienza.unibo.it/article/download/17350/16199
8
Book Review                                                                151
    Davide Bennato
Il computer come macroscopio. Big data e approccio computazionale per
comprendere i cambiamenti sociali e culturali. [The computer as a mac-
roscope. Big data and computational approaches to understand social
and cultural changes], Milano, Angeli, 2015, pp. 148

Tommaso Venturini Université de Lyon, Inria, ENS Lyon, CNRS,
UCB Lyon 1

     The Computer as a Macroscope is interesting book with a well-
defined angle. Rather than delivering the umpteenth prophecy on how
digital technologies will affect social life, the book describes how they al-
ready started to affect social research. Such angle (discussed in the first
chapter of the book) allows Davide Bennato to steer clear of the vast and
often shallow debate about the “digital age” and focus instead on the
specific approaches and techniques of computational social sciences.
     In its second chapter, the books focuses in particular on seven among
the main approaches of computational social sciences: 1. analytical soci-
ology (i.e. the effort to explain how global and long lasting structures are
produced by local and ephemeral interactions); 2. network sciences and
social network analysis (i.e. the investigation of the associations connect-
ing individual in complex collective patterns); 3. social simulation (i.e. the
struggle to understand social mechanisms by modelling them through
agent-based models); 4. mimetics (i.e. the study of the ‘viral’ spreading of
cultural items through media and especially social media); 5. cliometrics
(i.e. the quantitative study of long-term historical trends); 6. behavioural
economics (i.e. the use of experimental games, sometime in a digital form,
to investigate or predict dynamics of cooperation or competition); 7. cul-
turonomics and distant reading (i.e. the study of cultural and artistic phe-
nomena through the analysis of large corpora).
     The third chapter introduces four examples, allowing the readers to
gain a deeper understanding of this emerging approach. The cases dis-
cussed include several influential studies. It is a pity, however, that all the
examples concern traces extracted from social media (Facebook and
Twitter in particular) and analysed through network models. While this
type of studies does represent an important part of computational social
sciences, it is far from covering the variety of such field. The richness and
diversity of digital research, which is described in chapter 2, is here re-
duced to its most visible examples. This choice is unfortunate as much of
the interest of digital methods comes precisely from their capacity to di-
versify and open the imagination of social sciences. Against “big data”
prophecies, it is not the size of digital datasets that renews our under-
standing of the collective world, but their richness and variety. While the
jungle of digital inscription meets the eye for its extension, its most amaz-
152                                                          Tecnoscienza – 8 (1)

ing feature remains the stunning diversity of the species that it shelters.
     The book of Davide Bennato does a good job in portraying the chang-
ing field of computational social sciences in a way that is both accurate
and palatable. Instead of playing on the hype of big data and on the exot-
icism of computational research, it describes with plain words and vivid
examples the practices of this new discipline. The Computer as a Macro-
scope is not a book for experts, it does not discuss the latest develop-
ments of digital techniques or their theoretical consequences. To borrow
an expression from computer science, Bennato’s book is “breadth first”
(rather than “depth first”). Pushing the vanguard of digital sociology or
perfecting this or that method is not the purpose of this volume, which
strive instead to paint a wide portrait of the landscape of computational
social sciences. In this, Bennato achieves the goal: readers searching a
quick but exhaustive overview of this emerging research field will not be
disappointed. The book touches upon the most important strains of digi-
tal scholarship in a way that is sometime rapid, but never inaccurate.
     The main critique that could be addressed to The Computer as a
Macroscope, however, concern its rather positivist view of social sciences.
While Bennato introduces his work by observing that, in early modernity,
the development of quantification techniques has played key role in the
construction of our societies, he does not push his reflection to describe
how the new computational research is currently affecting our collective
life. He thoroughly describes the way in which digital technologies offers
new investigation tools, but does not discusses the societal impacts of the-
se research innovations. He introduced some of the most popular ap-
proaches of computational social sciences, but does not clarify which so-
cial visions are associated with them.
     This is why the metaphor contained in the title of this book is mislead-
ing. The concept of “macroscope” risks to convey an idea of digital tech-
nologies as mere “observation devices” – instruments allowing research-
ers to see phenomena invisible to the naked eye. This is true, but also re-
ductive. Besides being scientific instruments, digital technologies are also
powerful social actors and mediating infrastructures. They certainly make
the social more traceable, but they also do shape it in a variety of intend-
ed and unintended ways.
     Even when considered specifically under the angle of social sciences
(as in Bennato’s book), digital technologies are not just observation de-
vices, but also tools through which certain forms of collective coordina-
tion are promoted, while other are opposed. This type of is observation is
presented in an 8th strand of digital research, absent from Bennato’s book.
Developing a sort of meta-reflection on computational social sciences, a
number of researchers coming from the Science and Technology tradition
have extensively showed how, far from being neutral, digital methods are
associated with specific forms of visibility (cfr. among others, Bowker et
al. 2009; Law, Ruppert and Savage 2011; Rogers 2013; Marres 2017).
Book Review                                                                    153
More than to microscope or telescope observation, computational re-
search resembles to cartography in the 16th century (cfr. Turnbull 2000)
or demography in the 19th century (cfr. Desrosières 1993). As geography
and statistics supported the rise of the national state in its modern form
(cfr. Porter 1995), so the new computational research influences the way
in which we live, buy and vote – and such influence will no doubt grow in
the next years.
    This is why books like The Computer as a Macroscope are deeply
needed. Describing the emergence of new computational paradigms, they
help us reflecting on the many ways in which digital technologies affect
scientific research. This a very important contribution, but one that leaves
open the most important question of contemporary sociology: do we un-
derstand what forms of social organization are we promoting through our
computational research? And are we ready to stand by them?

References
Boullier, D. (2015) Vie et mort des sciences sociales avec le big data, “Socio”, 4,
        pp. 19-37.
Bowker, G.C., Baker, K., Millerand, F. and Ribes, D. (2009) Toward Information
      Infrastructure Studies: Ways of Knowing in a Networked Environment, in
      J. Hunsinger, L. Klastrup and M.M. Allen (eds.), International Handbook
      of Internet Research, Dordrecht, Springer, pp. 97-117.
Desrosières, A. (1993) La politique des grands nombres: Histoire de la raison
       statistique, Paris, La Découverte.
Law, J., Ruppert, E. and Savage, M. (2011) The double social life of methods,
       CRESC Working Paper.
Marres, N. (2017) Digital Sociology: The Reinvention of Social Research, Maden,
       Polity Press.
Porter, T.M. (1995) Trust in Numbers. The Pursuit of Objectivity in Science and
        Public Life, Princeton, Princeton University Press.
Rogers, R. (2013) Digital Methods, Cambridge, MA, MIT Press.
Turnbull, D. (2000) Masons, Tricksters and Cartographers, London, Routledge.



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