Sicily has played an important role in the development of the new research area named Econophysics. In fact some key ideas supporting this new hybrid discipline were originally formulated in a pioneering work of the Sicilian born physicist Ettore Maj
orana. The article he wrote was entitled The value of statistical laws in physics and social sciences. I will discuss its origin and history that has been recently discovered in the study of Stefano Roncoroni. This recent study documents the true reasons and motivations that triggered the pioneering work of Majorana. It also shows that the description of this work provided by Edoardo Amaldi was shallow and misleading. In the second part of the talk I will recollect the first years of development of econophysics and in particular the role of the International Workshop on Econophysics and Statistical Finance held in Palermo on 28-30 September 1998 and the setting in 1999 of the Observatory of Complex Systems the research group on Econophysics of Palermo University and Istituto Nazionale di Fisica della Materia.
We present an analysis of the credit market of Japan. The analysis is performed by investigating the bipartite network of banks and firms which is obtained by setting a link between a bank and a firm when a credit relationship is present in a given t
ime window. In our investigation we focus on a community detection algorithm which is identifying communities composed by both banks and firms. We show that the clusters obtained by directly working on the bipartite network carry information about the networked nature of the Japanese credit market. Our analysis is performed for each calendar year during the time period from 1980 to 2011. Specifically, we obtain communities of banks and networks for each of the 32 investigated years, and we introduce a method to track the time evolution of these communities on a statistical basis. We then characterize communities by detecting the simultaneous over-expression of attributes of firms and banks. Specifically, we consider as attributes the economic sector and the geographical location of firms and the type of banks. In our 32 year long analysis we detect a persistence of the over-expression of attributes of clusters of banks and firms together with a slow dynamics of changes from some specific attributes to new ones. Our empirical observations show that the credit market in Japan is a networked market where the type of banks, geographical location of firms and banks and economic sector of the firm play a role in shaping the credit relationships between banks and firms.
Big data open up unprecedented opportunities to investigate complex systems including the society. In particular, communication data serve as major sources for computational social sciences but they have to be cleaned and filtered as they may contain
spurious information due to recording errors as well as interactions, like commercial and marketing activities, not directly related to the social network. The network constructed from communication data can only be considered as a proxy for the network of social relationships. Here we apply a systematic method, based on multiple hypothesis testing, to statistically validate the links and then construct the corresponding Bonferroni network, generalized to the directed case. We study two large datasets of mobile phone records, one from Europe and the other from China. For both datasets we compare the raw data networks with the corresponding Bonferroni networks and point out significant differences in the structures and in the basic network measures. We show evidence that the Bonferroni network provides a better proxy for the network of social interactions than the original one. By using the filtered networks we investigated the statistics and temporal evolution of small directed 3-motifs and conclude that closed communication triads have a formation time-scale, which is quite fast and typically intraday. We also find that open communication triads preferentially evolve to other open triads with a higher fraction of reciprocated calls. These stylized facts were observed for both datasets.
