社会预测:美国国家安全系统推动的人类行为模型研究的文献综述

Q4 Social Sciences
R. F. Maciel, Marta Macedo Kerr Pinheiro, P. Bayerl
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引用次数: 1

摘要

新的信息和通信技术的发展增加了社会内部信息流的数量。对于安全部队来说,这种现象为收集、处理和分析与收集大量不同数据有关的信息提供了新的机会,同时需要新的组织和个人能力来处理新形式和大量信息。我们的研究旨在概述由美国国防和情报机构资助的关于社会预测的研究领域。基于文献计量学技术,我们将2688篇由美国国防或情报机构资助的文章聚类在五个研究领域:a)复杂网络,b)社会网络,c)人类推理,d)优化算法和e)神经科学。之后,我们定性地分析了每个领域被引次数最多的论文。我们的分析表明,这些研究领域与美国的情报原则是一致的。除此之外,我们认为,只要提供基本训练,这些研究领域可以纳入安全部队的工作。基础培训不仅可以提高执法机构的能力,还有助于防止数据分析中的(无意识的)偏见和错误。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SOCIAL FORECASTING: A literature review of research promoted by the United States National Security System to model human behavior
The development of new information and communication technologies increased the volume of information flows within society. For the security forces, this phenomenon presents new opportunities for collecting, processing and analyzing information linked with the opportunity to collect a vast and diverse amount data, and at the same time it requires new organizational and individual competences to deal with the new forms and huge volumes of information. Our study aimed to outline the research areas funded by the US defense and intelligence agencies with respect to social forecasting. Based on bibliometric techniques, we clustered 2688 articles funded by US defense or intelligence agencies in five research areas: a) Complex networks, b) Social networks, c) Human reasoning, d) Optimization algorithms, and e) Neuroscience. After that, we analyzed qualitatively the most cited papers in each area. Our analysis identified that the research areas are compatible with the US intelligence doctrine. Besides that, we considered that the research areas could be incorporated in the work of security forces provided that basic training be offered. The basic training would not only enhance capabilities of law enforcement agencies but also help safeguard against (unwitting) biases and mistakes in the analysis of data.
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来源期刊
CiteScore
0.10
自引率
0.00%
发文量
45
审稿时长
10 weeks
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