Social Network Analysis (SNA): Can identities and frontiers be modeled and correlated through IT/AI?

The M@GM@ Journal has recently issued a call for contributions entitled ”L’IDENTIT ´E: QUAND LES FRONTI `ERES SE REDESSINENT”. According to the contents of the above-mentioned call, identity (whether social, group or individual) is revealed as a function of an unstable and dynamically evolving system, dependent on different random variables in a non-deterministic force field that cannot be immediately determined on a small scale, but which can present repetitive structures on a large and very large scale. Therefore, fractal structures were considered that could be determined through their analogies by analyzing the entire scale of the variables and of the identity function. In short, the topic should be dominated by Juli`a’s laws and the Attractor model. If this were agreed upon, models and a multivariate function could be suggested to betaken as a reference in the more general study of problems concerning identity and frontiers. However, the analysis highlights that the direct or indirect presence of the human factor, with its intrinsic unpredictability and irreducible, seems to impact on the possible analyses and modeling through IT/AI that are potentially set up as in the review outlined here. At least at first glance, mathematical modeling appears possible, but above all to develop similarities and reasoning in an analogical way, rather than to reach defined and quantitative results, unless it proceeds through research and development of concrete application examples. Different, instead, are the perspectives through a complementary and synergic approach of SNA and mathematical modeling together. In practice, SNA can provide experimental datasets and trends at different times to buildand calibrate the proposed differential equations! Without this calibration, the mathematical modeling proposal would be purely theoretical.