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A clustering view on ESS measures of political interest: an EM-MML approach

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Detalhes bibliográficos
Resumo:In this work, we perform the clustering of European regions, based on their citizens’ political interests and electoral participation, as expressed in data from the two most recent European Social Surveys (ESS) - 2012 (round 6) and 2014 (round 7). We resort to a new clustering approach, named EM-MML, which clusters categorical data and simultaneously determines the number of clusters. Clustering is applied to sets of questions referring to whether the citizens were involved in “different ways of trying to improve things in their country or help prevent things from going wrong” – e.g., signed a petition or worked in a political organisation or association. The results of the EM-MML approach are compared with results from the classical EM approach combined with several information criteria. EM-MML approach provides more parsimonious and robust solutions than those obtained by standard EM and it is also faster than the other methods considered, which is especially relevant when dealing with large data sets.
Autores principais:Silvestre, Cláudia
Outros Autores:Cardoso, Margarida; Figueiredo, Mário
Assunto:Official statistics Categorical data Clustering EM-MML algorithm European Social Survey Finite mixture models
Ano:2017
País:Portugal
Tipo de documento:documento de conferência
Tipo de acesso:acesso aberto
Instituição associada:Instituto Politécnico de Lisboa
Idioma:inglês
Origem:Repositório Científico do Instituto Politécnico de Lisboa
Descrição
Resumo:In this work, we perform the clustering of European regions, based on their citizens’ political interests and electoral participation, as expressed in data from the two most recent European Social Surveys (ESS) - 2012 (round 6) and 2014 (round 7). We resort to a new clustering approach, named EM-MML, which clusters categorical data and simultaneously determines the number of clusters. Clustering is applied to sets of questions referring to whether the citizens were involved in “different ways of trying to improve things in their country or help prevent things from going wrong” – e.g., signed a petition or worked in a political organisation or association. The results of the EM-MML approach are compared with results from the classical EM approach combined with several information criteria. EM-MML approach provides more parsimonious and robust solutions than those obtained by standard EM and it is also faster than the other methods considered, which is especially relevant when dealing with large data sets.