The road to democracy: modeling and analysis of an election big data

J. Akaichi
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引用次数: 1

Abstract

Various organizations, such as those active in business or in politics, capture, store, and analyze data gathered from heterogeneous, distributed, and sometimes autonomous information sources including social media, classical and Web databases, multimedia files, localization raw data, etc. Big data is a term used to describe such kind of data having high volume, velocity, and variety features. It involves innovative technologies, such as pervasive and cloud computing ones, used to enhance decision making, provide vision, discovery, and backing to improve business processes and actions on the ground. The latent value of big data analytics is prodigious and clearly recognized by a rising number of studies such as topics related to politics. The tutorial will focus, in general, on big data and related analytics rising topics, and, in particular, on big data studies performed in the modern democracy era. Modeling and analysis approaches will be discussed, and various cases of election big data, including experiences performed in old democracies such in the United States, Canada, and the new ones such in Tunisia, will be presented.
民主之路:选举大数据的建模与分析
各种组织(例如活跃于商业或政治领域的组织)捕获、存储和分析从异构的、分布式的(有时是自治的)信息源收集的数据,这些信息源包括社会媒体、经典数据库和Web数据库、多媒体文件、本地化原始数据等。大数据是一个术语,用来描述具有高容量、高速度和多样性特征的数据。它涉及创新技术,例如普及和云计算技术,用于增强决策制定,提供远景、发现和支持,以改进业务流程和实际操作。大数据分析的潜在价值是巨大的,越来越多的研究都清楚地认识到这一点,比如与政治相关的话题。本教程将重点关注大数据和相关分析的新兴话题,特别是在现代民主时代进行的大数据研究。将讨论建模和分析方法,并介绍选举大数据的各种案例,包括在美国、加拿大等老牌民主国家和突尼斯等新兴民主国家的经验。
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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