The growing and progressive decrease in voter turnout af- fects almost all established democracies and all types of electoral con- sultations, albeit with different intensities. The aim of the paper is to identify which cultural and socio-economic factors may contribute to ex- plain the voter turnout in the 2022 Italian parliamentary election. The determinants of non-voting are identified using data from the European Social Survey through a graphical modeling approach based on Bayesian networks.
Data-Driven Analysis of No-Vote Rates Using Bayesian Networks / Marella, D., Musella, F., Vicard, P.. - (2026). (SIS-FENStatS 2026 2026 roma ).
Data-Driven Analysis of No-Vote Rates Using Bayesian Networks.
Marella D.;Vicard P.
2026
Abstract
The growing and progressive decrease in voter turnout af- fects almost all established democracies and all types of electoral con- sultations, albeit with different intensities. The aim of the paper is to identify which cultural and socio-economic factors may contribute to ex- plain the voter turnout in the 2022 Italian parliamentary election. The determinants of non-voting are identified using data from the European Social Survey through a graphical modeling approach based on Bayesian networks.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
