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

• Autor(a) principal: Silvestre, Cláudia
• Data de Publicação: 2017
• Outros Autores: Cardoso, Margarida, Figueiredo, Mário
• Idioma: eng
• Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Texto Completo: http://hdl.handle.net/10400.21/7689
• topic: Official statistics; Categorical data; Clustering; EM-MML algorithm; European Social Survey; Finite mixture models

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.