We make use of an advanced artificial neural network (Auto-CM) to model the structure of the current world order as a data-driven reconstruction of the implicit relationships between countries and of their time evolution, as derived from a database of publicly observable socioeconomic and political variables. Building on previous research, we analyze 93 variables derived from dozens of key indicators for 128 countries and trace their evolution along a period of eight years, 2007–2014. We find evidence of an increasing structural instability that seems to signal a transition toward a new, as yet undetermined, multipolar world order.

Global world (dis-)order? Analyzing the dynamic evolution of the micro-structure of multipolarism by means of an unsupervised neural network approach, 2021.

Global world (dis-)order? Analyzing the dynamic evolution of the micro-structure of multipolarism by means of an unsupervised neural network approach

Ferilli, Guido;Sacco, Pier Luigi;
2021-01-01

Abstract

We make use of an advanced artificial neural network (Auto-CM) to model the structure of the current world order as a data-driven reconstruction of the implicit relationships between countries and of their time evolution, as derived from a database of publicly observable socioeconomic and political variables. Building on previous research, we analyze 93 variables derived from dozens of key indicators for 128 countries and trace their evolution along a period of eight years, 2007–2014. We find evidence of an increasing structural instability that seems to signal a transition toward a new, as yet undetermined, multipolar world order.
Inglese
2021
121351
18
internazionale
esperti anonimi
con ISI Impact Factor
A stampa
Settore SECS-P/01 - Economia Politica
Settore SECS-P/06 - Economia Applicata
6
File in questo prodotto:
File Dimensione Formato  
TFSC 2021.pdf

Accessibile solo dagli utenti con account Apeiron

Tipologia: Documento in Pre-print
Dimensione 7.25 MB
Formato Adobe PDF
7.25 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10808/40983
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? 4
social impact