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1948年至2018年意大利选举中投票的熵分析。

Entropic Analysis of Votes Expressed in Italian Elections between 1948 and 2018.

作者信息

Marmani Stefano, Ficcadenti Valerio, Kaur Parmjit, Dhesi Gurjeet

机构信息

Business School, London South Bank University, 103 Borough Road, London SE1 0AA, UK.

Leicester Castle Business School, De Montfort University, Leicester LE1 9BH, UK.

出版信息

Entropy (Basel). 2020 May 4;22(5):523. doi: 10.3390/e22050523.

Abstract

In Italy, the elections occur often, indeed almost every year the citizens are involved in a democratic choice for deciding leaders of different administrative entities. Sometimes the citizens are called to vote for filling more than one office in more than one administrative body. This phenomenon has occurred 35 times after 1948; it creates the peculiar condition of having the same sample of people expressing decisions on political bases at the same time. Therefore, the Italian contemporaneous ballots constitute the occasion to measure coherence and chaos in the way of expressing political opinion. In this paper, we address all the Italian elections that occurred between 1948 and 2018. We collect the number of votes per party at each administrative level and we treat each election as a manifestation of a complex system. Then, we use the Shannon entropy and the Gini Index to study the degree of disorder manifested during different types of elections at the municipality level. A particular focus is devoted to the contemporaneous elections. Such cases implicate different disorder dynamics in the contemporaneous ballots, when different administrative level are involved. Furthermore, some features that characterize different entropic regimes have emerged.

摘要

在意大利,选举频繁举行,实际上几乎每年公民都会参与民主选择,以决定不同行政实体的领导人。有时,公民会被要求在多个行政机构中为填补不止一个职位而投票。1948年之后这种情况出现了35次;这就产生了一种特殊情况,即同一批人同时基于政治立场做出决策。因此,意大利的同步投票为衡量表达政治观点方式中的一致性和混乱程度提供了契机。在本文中,我们研究了1948年至2018年间意大利举行的所有选举。我们收集了每个行政级别上各政党的选票数量,并将每次选举视为一个复杂系统的表现形式。然后,我们使用香农熵和基尼指数来研究在市镇层面不同类型选举中表现出的无序程度。特别关注同步选举。当涉及不同行政级别时,此类情况在同步投票中蕴含着不同的无序动态。此外,还出现了一些表征不同熵状态的特征。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2161/7517014/cf15484452d2/entropy-22-00523-g001.jpg

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