CLUSTERING OF UKRAINIAN REGIONS BASED ON VALUE ORIENTATIONS AND POLITICAL CHOICE OF THE POPULATIONS: METHODOLOGICAL RATIONALE AND ANALYSIS USING COMBINING DATA SOURCES
{"title":"CLUSTERING OF UKRAINIAN REGIONS BASED ON VALUE ORIENTATIONS AND POLITICAL CHOICE OF THE POPULATIONS: METHODOLOGICAL RATIONALE AND ANALYSIS USING COMBINING DATA SOURCES","authors":"","doi":"10.36004/nier.es.2019.1-10","DOIUrl":null,"url":null,"abstract":"The aim of this study is clustering of administrative-territorial units of Ukraine on the basis of value orientations and the electoral choice of the population of these units. The k-means method is used. Creation of macroregions basing on the political orientations of the population is quite widespread, but such approaches have a number of limitations, primarily due to the fact that the list of political leaders or political parties can change significantly in rather short periods of time and because of difficulties with using of several political parties/leaders simultaneously in the analysis. \nThe «value» in this article is defined within Schwartz's theory as desirable goals that go beyond specific situations, differ in importance from each other and are guiding principles in human life. The analysis uses the ten Schwartz's values, which are grouped into four dimensions: «Conservation», «Self-Enhancement», «Self-Transcendence» and «Openness to Change». The data set for this study is combination of two sources of data – sample survey and electoral statistics. Thus, the data set in this study is formed by a combination of the results of the Ukrainian vote in the Parliamentary elections in 2012 and sample survey – European Social Survey – the latest wave of which was held in Ukraine in 2012. The European Social Survey is the most actual source of data on the value orientations of Ukrainians which is in free access. After 2012 this study in Ukraine was no longer conducted.\nThe main result of this study is the creation of clusters of administrative-territorial units based on the similarity of the results of voting and value orientations of population in these units. The first cluster includes administrative-territorial units, where population has more expressed values of Self-transcendence than in Ukraine as a whole. In the second cluster there are units where population has more expressed values of Self-enhancement and Openness to change. The third cluster is characterized by more expressive values of Self-transcendence and Conservation. Except of different levels of expression values, clusters differ by the level of support of political parties that participated in Parliamentary elections. \nThis approach allows evaluate the received cluster structure in dynamics, use in analysis results of national and local elections in different years. Also it makes clustering space two-dimensional, which enables not only to discover similar administrative-territorial units, but also, for example, to identify groups of parties whose supporters share similar values. Although the article uses data from 2012, the successful application of this approach to the clustering of administrative-territorial units opens up the ways for such clustering on more recent data.","PeriodicalId":30515,"journal":{"name":"Economy and Sociology","volume":"29 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Economy and Sociology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36004/nier.es.2019.1-10","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The aim of this study is clustering of administrative-territorial units of Ukraine on the basis of value orientations and the electoral choice of the population of these units. The k-means method is used. Creation of macroregions basing on the political orientations of the population is quite widespread, but such approaches have a number of limitations, primarily due to the fact that the list of political leaders or political parties can change significantly in rather short periods of time and because of difficulties with using of several political parties/leaders simultaneously in the analysis.
The «value» in this article is defined within Schwartz's theory as desirable goals that go beyond specific situations, differ in importance from each other and are guiding principles in human life. The analysis uses the ten Schwartz's values, which are grouped into four dimensions: «Conservation», «Self-Enhancement», «Self-Transcendence» and «Openness to Change». The data set for this study is combination of two sources of data – sample survey and electoral statistics. Thus, the data set in this study is formed by a combination of the results of the Ukrainian vote in the Parliamentary elections in 2012 and sample survey – European Social Survey – the latest wave of which was held in Ukraine in 2012. The European Social Survey is the most actual source of data on the value orientations of Ukrainians which is in free access. After 2012 this study in Ukraine was no longer conducted.
The main result of this study is the creation of clusters of administrative-territorial units based on the similarity of the results of voting and value orientations of population in these units. The first cluster includes administrative-territorial units, where population has more expressed values of Self-transcendence than in Ukraine as a whole. In the second cluster there are units where population has more expressed values of Self-enhancement and Openness to change. The third cluster is characterized by more expressive values of Self-transcendence and Conservation. Except of different levels of expression values, clusters differ by the level of support of political parties that participated in Parliamentary elections.
This approach allows evaluate the received cluster structure in dynamics, use in analysis results of national and local elections in different years. Also it makes clustering space two-dimensional, which enables not only to discover similar administrative-territorial units, but also, for example, to identify groups of parties whose supporters share similar values. Although the article uses data from 2012, the successful application of this approach to the clustering of administrative-territorial units opens up the ways for such clustering on more recent data.
本研究的目的是根据价值取向和这些单位的人口的选举选择对乌克兰的行政领土单位进行聚类。使用k-means方法。根据人口的政治倾向建立宏观区域的做法相当普遍,但这种做法有一些局限性,主要是因为政治领导人或政党的名单可以在相当短的时间内发生重大变化,也因为在分析中同时使用几个政党/领导人有困难。本文中的“价值”在施瓦茨的理论中被定义为超越特定情况的理想目标,彼此的重要性不同,并且是人类生活的指导原则。该分析使用了施瓦茨的十个价值观,将其分为四个维度:“保护”、“自我提升”、“自我超越”和“开放变革”。本研究的数据集是抽样调查和选举统计两种数据来源的结合。因此,本研究的数据集是由2012年乌克兰议会选举的投票结果和2012年在乌克兰举行的最新一波抽样调查——欧洲社会调查(European Social survey)——相结合而形成的。欧洲社会调查是关于乌克兰人价值取向的最实际的数据来源,它是免费获取的。2012年之后,乌克兰的这项研究不再进行。本研究的主要结果是基于这些单位的投票结果和人口价值取向的相似性,创建了行政领土单位集群。第一个集群包括行政领土单位,那里的人口比整个乌克兰更能表达自我超越的价值观。在第二个集群中,人口更多地表达了自我提升和对变化开放的价值观。第三个群体的特点是自我超越和保守的表达价值。除了表达价值水平不同外,参与议会选举的政党的支持程度也不同。这种方法可以评估收到的动态集群结构,用于分析不同年份的国家和地方选举结果。此外,它使集群空间成为二维的,这不仅可以发现相似的行政领土单位,而且还可以识别支持者拥有相似价值观的政党团体。尽管本文使用的是2012年的数据,但将这种方法成功应用于行政领土单位的聚类,为在更近期的数据上进行此类聚类开辟了道路。