Predicting party switching through machine learning and open data.
Ontology highlight
ABSTRACT:
SUBMITTER: Meneghetti N
PROVIDER: S-EPMC10319836 | biostudies-literature | 2023 Jul
REPOSITORIES: biostudies-literature
Publications
Predicting party switching through machine learning and open data.
Meneghetti Nicolò N Pacini Fabio F Biondi Dal Monte Francesca F Cracchiolo Marina M Rossi Emanuele E Mazzoni Alberto A Micera Silvestro S
iScience 20230614 7
Parliament dynamics might seem erratic at times. Predicting future voting patterns could support policy design based on the simulation of voting scenarios. The availability of open data on legislative activities and machine learning tools might enable such prediction. In our paper, we provide evidence for this statement by developing an algorithm able to predict party switching in the Italian Parliament with over 70% accuracy up to two months in advance. The analysis was based on voting data fro ...[more]
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