Presentation at ASIST 2016 -- Michael Marcinkowski.

1. The ideological problematic
of (big) data and Social
Informatics
An analytic discussion and one example
Michael Marcinkowski : m.marcinkowski@bathspa.ac.uk

2. “To identify the social impacts of computing, one must
have, at least implicitly, a theory of the causal
powers that computerized systems can exert upon
individuals, groups, organizations, institutions, social
networks, social worlds, and other social entities” [4, p.
62].
Michael Marcinkowski : m.marcinkowski@bathspa.ac.uk

3. “[T]he empirical objects of social
informatics can be as much
conceptual constructs as empirical
entities” [1, p. 576].
Michael Marcinkowski : m.marcinkowski@bathspa.ac.uk

4. Michael Marcinkowski : m.marcinkowski@bathspa.ac.uk
Empirical Critical

5. Michael Marcinkowski : m.marcinkowski@bathspa.ac.uk
Empirical Critical
(Big) Data

6. Michael Marcinkowski : m.marcinkowski@bathspa.ac.uk
Empirical Critical
(Big) Data(Big) Data
(Movements of computerization
and dataization [5])

7. Michael Marcinkowski : m.marcinkowski@bathspa.ac.uk
Empirical Critical
(Big) Data(Big) Data
(Movements of computerization
and dataization [5])
(Hyper-theoretical and a-
theoretical [3])

8. Computerization Movements
Michael Marcinkowski : m.marcinkowski@bathspa.ac.uk

9. Computerization Movements
Dataization Movements
Michael Marcinkowski : m.marcinkowski@bathspa.ac.uk

10. Empiricism
Michael Marcinkowski : m.marcinkowski@bathspa.ac.uk
Subject Object
Data

11. “Peak Empiricism” [6]
Michael Marcinkowski : m.marcinkowski@bathspa.ac.uk
Subject Object
Data

12. Ambient Literature
“[W]hat might happen when data aspires to literary form” [2, p. 140].
Michael Marcinkowski : m.marcinkowski@bathspa.ac.uk

13. References
1. Day, R. E. (2007). Kling and the “critical”: Social informatics and critical informatics. Journal of the American Society
for Information Science and Technology, 58(4), 575–582. https://doi.org/10.1002/asi.20546
2. Dovey, J. (2016). Ambient Literature: Writing Probability. In U. Ekman, J. D. Bolter, L. Diaz, M. Søndergaard, & M.
Engberg (Eds.), Ubiquitous Computing, Complexity and Culture (pp. 141–154). New York, NY: Routledge.
3. Fonseca, F., & Marcinkowski, M (2016). Has (big) data already won? In: International Symposium on Science of
Science, 22-23 March 2016, Library of Congress, Washington DC, USA.
4. Kling, R. (1980). Social analyses of computing: theoretical perspectives in recent empirical research. ACM
Computing Surveys, 12(1), 61–110. https://doi.org/10.1145/356802.356806
5. Marcinkowski, M. (2016). Data, ideology, and the developing critical program of social informatics. Journal of the
Association for Information Science and Technology, 67(5), 1266–1275. https://doi.org/10.1002/asi.23483
6. Marcinkowski, M., & Fonseca, F. (2016). The conditions of peak empiricism in big data and interaction design.
Journal of the Association for Information Science and Technology, 67(6), 1279–1288.
https://doi.org/10.1002/asi.23497
Michael Marcinkowski : m.marcinkowski@bathspa.ac.uk