The possibilities of using machine learning methods to solve political problems

S. Erokhin, A. V. Vanushina, O. Erokhina
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引用次数: 1

Abstract

political reality is characterized by nonlinearity of processes and significant influence not only of formal, but also shadow mechanisms of interaction of the actors taking decisions - political elites and leaders. One of the most promising areas, which opens up new opportunities for studying political problems, is the synthesis of the “traditional” methodology of political analysis and methods of artificial intelligence. The paper substantiates the adequacy of the use of a decision tree for analyzing and forecasting political decisions by the example of the personnel policy of federal structures in relation to the regions of the Russian Federation.
利用机器学习方法解决政治问题的可能性
政治现实的特点是过程的非线性,不仅受到正式的影响,而且还受到决策行为者(政治精英和领导人)相互作用的影子机制的影响。最有前途的领域之一是将政治分析的“传统”方法论与人工智能方法相结合,这为研究政治问题开辟了新的机会。本文以联邦结构与俄罗斯联邦各地区有关的人事政策为例,证实了利用决策树分析和预测政治决定的适当性。
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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