Abstract
Starting from the conceptualization of ‘Cluster Index’ (CI), Villani et al. [16, 17] implemented the ‘Dynamic Cluster Index’ (DCI), an algorithm to perform the detection of subsets of agents characterized by patterns of activity that can be considered as integrated over time. DCI methodology makes possible to shift the attention into a new dimension of groups of agents (i.e. communities of agents): the presence of a common function characterizing their actions. In this paper we discuss the implications of the use in the domain of social sciences of this methodology, up to now mainly applied in natural sciences. Developing our considerations thanks to an empirical analysis, we discuss the theoretical implications of its application in such a different field.
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Notes
- 1.
In the field of neurological activity, two theories have always been opposed: the first, a localizationist theory sustains that the brain is divided into separate areas characterized by specific functions, while the second sustains the presence of a holistic scheme of the brain activity. Neither of these formulations were compatible with the hypothesis of the presence of groups of neurons that, regardless of their position, have specific and common functions.
- 2.
A homogeneous system is a system having the same number of variables of the system to which it is referred; each variable has a random generated behavior in accordance with the probability of the states it assumes in the reference system.
References
Caloffi, A., Rossi, F., Russo, M.: The emergence of intermediary organizations: a network-based approach to the design of innovation policies. In: Handbook On Complexity And Public Policy, pp. 314–331. Edward Elgar Publishing, Cheltenham GBR (2015). ISBN: 978-1-78254-951-2
Caloffi, A., Rossi, F., Russo, M.: What makes SMEs more likely to collaborate? Analysing the role of regional innovation policy. Eur. Plan. Stud. 23(7), 1245–1264 (2015). http://dx.doi.org/10.1080/09654313.2014.919250
Filisetti, A., Villani, M., Roli, A., Fiorucci, M., Serra, R.: Exploring the organisation of complex systems through the dynamical interactions among their relevant subsets. In: Proceedings of the European Conference on Articial Life 2015 (ECAL 2015), vol. 13, pp. 286–293 (2016). https://mitpress.mit.edu/sites/default/files/titles/content/ecal2015/ch054.html
Hidalgo, C.: Why Information Grows: The Evolution of Order, from Atoms to Economies. Basic Books, New York (2015)
Lane, D.A.: Complexity and innovation dynamics. In: Handbook on the Economic Complexity of Technological Change. Edward Elgar Publishing, Cheltenham (2011). ISBN: 978-0-85793-037-8
Lane, D.A., Maxfield, R.R.: Foresight, complexity, and strategy. In: The Economy as an Evolving Complex System II. Westview Press (1997). ISBN: 978-0-201-32823-3
Lane, D.A., Maxfield, R.R.: Ontological uncertainty and innovation. J. Evol. Econ. 15(1), 3–50 (2005). doi:10.1007/s00191-004-0227-7
Roli, A., Villani, M., Caprari, R., Serra, R.: Identifying critical states through the relevance index. Entropy 19(2), 73 (2017). Special issue: Complexity, Criticality and Computation, MDPI AG, Basel, Switzerland
Rossi, F., Caloffi, A., Russo, M.: Networked by design: can policy requirements influence organisations’ networking behaviour? Technol. Forecast. Soc. Change 105, 203–214 (2016). doi:10.1016/j.techfore.2016.01.004
Russo, M., Caloffi, A., Rossi, F.: Evaluating the performance of innovation intermediaries: insights from the experience of Tuscany’s innovation poles. In: Plattform Forschungs- Und Technologieevaluierung, vol. 41, pp. 15–25 (2015). ISSN: 1726–6629
Russo, M., Rossi, F.: Cooperation networks and innovation. A complex system perspective to the analysis and evaluation of a EU regional innovation policy programme. Evaluation 15, 75–100 (2009). doi:10.1177/1356389008097872
Tononi, G., McIntosh, A.R., Russell, D.P., Edelman, G.M.: Functional clustering: identifying strongly interactive brain regions in neuroimaging data. NeuroImage 7(2), 133–149 (1998). doi:10.1006/nimg.1997.0313
Tononi, G., Sporns, O., Edelman, G.M.: A complexity measure for selective matching of signals by the brain. Proc. Natl. Acad. Sci. USA 93(8), 3422–3427 (1996). ISSN: 0027–8424
Tononi, G., Sporns, O., Edelman, G.M.: A measure for brain complexity: relating functional segregation and integration in the nervous system. Proc. Natl. Acad. Sci. USA 91(11), 5033–5037 (1994). http://www.jstor.org/stable/2364906. ISSN: 0027–8424
Tononi, G., Sporns, O., Edelman, G.M.: Measures of degeneracy and redundancy in biological networks. Proc. Natl. Acad. Sci. 96(6), 3257–3262 (1999). http://www.pnas.org/content/96/6/3257. ISSN: 0027–8424,1091–6490
Villani, M., Benedettini, S., Roli, A., Lane, D., Poli, I., Serra, R.: Identifying emergent dynamical structures in network models. In: Bassis, S., Esposito, A., Morabito, F.C. (eds.) Recent Advances of Neural Network Models and Applications. Smart Innovation, Systems and Technologies, vol. 26, pp. 3–13. Springer, Cham (2014). doi:10.1007/978-3-319-04129-2_1
Villani, M., Filisetti, A., Benedettini, S., Roli, A., Lane, D., Serra, R.: The detection of intermediate-level emergent structures and patterns. In: ECAL, pp. 372–378 (2013)
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Righi, R., Roli, A., Russo, M., Serra, R., Villani, M. (2017). New Paths for the Application of DCI in Social Sciences: Theoretical Issues Regarding an Empirical Analysis. In: Rossi, F., Piotto, S., Concilio, S. (eds) Advances in Artificial Life, Evolutionary Computation, and Systems Chemistry. WIVACE 2016. Communications in Computer and Information Science, vol 708. Springer, Cham. https://doi.org/10.1007/978-3-319-57711-1_4
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