Election Forensics: Quantitative methods for electoral fraud detection
Election Forensics: Quantitative methods for electoral fraud detection
复制标题
DOI：
10.1016/j.forsciint.2018.11.010
复制
发表时间：
2019-01-01
影响因子：
2.2
通讯作者：
Fernandez-Gracia, Juan
中科院分区：
文献类型：
--
作者：
Lacasa, Lucas;Fernandez-Gracia, Juan
在过去的十年里，计算能力的爆炸式增长和对大量数据集的访问的并行增加-所谓的大数据范式-这使得能够开发全新的定量策略，以支持对复杂场景的描述，理解和控制。一个有趣的应用领域涉及从在线数据中检测欺诈，更具体地说，从选举活动的大量数字指纹中提取有意义的信息，以检测欺诈行为的后验证据。在这篇短文中，我们讨论了近年来在这方面出现的一些定量方法，这些方法共同形成了选举法医学的新兴跨学科领域。为了促进讨论和提高对这一跨学科领域的认识，我们在此列举了一些最相关的方法和途径。(C)2018爱思唯尔B. V.保留所有权利。
The last decade has witnessed an explosion on the computational power and a parallel increase of the access to large sets of data - the so called Big Data paradigm - which is enabling to develop brand new quantitative strategies underpinning description, understanding and control of complex scenarios. One interesting area of application concerns fraud detection from online data, and more particularly extracting meaningful information from massive digital fingerprints of electoral activity to detect, a posteriori, evidence of fraudulent behavior. In this short article we discuss a few quantitative methodologies that have emerged in recent years on this respect, which altogether form the nascent interdisciplinary field of election forensics. Aiming to foster discussion and raise awareness on this interdisciplinary area, we hereby enumerate a few of the most relevant approaches and methods. (C) 2018 Elsevier B.V. All rights reserved.