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Learning Political DNA in the Italian Senate

Conference Paper
Publication Date:
2019
abstract:
Motivated by the increasing interest of the control community towards social sciences and the study of opinion formation and belief systems, in this paper we address the problem of exploiting voting data for inferring the underlying affinity of individuals to competing ideology groups.
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
belief networks; data analysis; feature extraction; government data processing; learning (artificial intelligence); legislation; politics; probability; random processes
List of contributors:
Dabbene, Fabrizio; Ravazzi, Chiara
Authors of the University:
DABBENE FABRIZIO
RAVAZZI CHIARA
Handle:
https://iris.cnr.it/handle/20.500.14243/403171
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