Clustering of Polish Citizens on the Bases of Their Support for Leaving and Remaining the European Union

Artur Roland Kozłowski, Grzegorz Krzykowski, Grahame Fallon
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引用次数: 0

Abstract

The article presents the clustering of Polish citizens based on the empirical dimension of support for European integration. The structure of the work is based on three key elements constituting the basis of the presented text. The first refers to the development of a scale to measure the extent of support for the integration of Poland with the EU. The second element covers an area of support scale modelling. After the substantial and statistical analysis of the adequacy of the probability distribution for the support scale, it was decided that a model in which the scale underwent mixing non-standard Beta distributions would be adopted. Applying the Maximal Likelihood Method (ML), the components for its fitted probability densities and estimators of prior (or mixing) probabilities were indicated. The procedure allowed us to define the clusters of which the population of voters was composed. The paper’s final section presents many practical and theoretical conclusions for political parties and scientists interested in the discussed area. The novelty of applying the ML method goes hand in hand with the findings that previously appeared in political science literature, although under different economic and geopolitical conditions.
支持脱欧和留欧的波兰公民聚集
本文基于支持欧洲一体化的实证维度,提出波兰公民的聚类。该作品的结构是基于构成本文基础的三个关键要素。第一个是制定一个量表来衡量波兰与欧盟一体化的支持程度。第二个要素涵盖了一个支持比例建模的领域。在对支持量表概率分布的充分性进行了大量的统计分析后,决定采用混合非标准Beta分布的模型。应用极大似然法(ML),给出了其拟合概率密度的分量和先验(或混合)概率的估计量。这个程序使我们能够确定组成选民总数的组。论文的最后一部分为对讨论领域感兴趣的政党和科学家提供了许多实践和理论结论。应用机器学习方法的新颖性与先前出现在政治学文献中的发现密切相关,尽管是在不同的经济和地缘政治条件下。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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19
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10 weeks
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