An innovative color-coding scheme for terrorism threat advisory system

Q1 Social Sciences
P. Singh, Deepu Philip
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引用次数: 1

Abstract

This research develops an innovative terror threat advisory system capable of visually communicating variations in the terrorism levels to policymakers or the public and forecasts future levels. Earlier attempts to create similar advisory systems by policymakers were either discontinued or lost their relevance due to a trust deficit in the system. We propose a novel approach for creating a color scheme and utilize it to develop an intuitive caterpillar diagram summarizing various stages of terrorism. It incorporates Global Terrorism Impact Scores for a nation or region using the Global Terrorism Database (GTD). Further, color transitions in the caterpillar diagram between consecutive periods mimic a Markovian process, thereby enabling us to develop the forecasting model. We successfully demonstrated the effectiveness of the proposed caterpillar diagram and forecasting model for India, Iraq, and their respective regions. The forecasting model suggests that the aggressive terrorism stage depicted by red color and transient stages of ascent (yellow) and descent (cyan) are the most probable in these nations and their regions. The proposed caterpillar diagram is an innovative visualization approach to identify terrorism patterns, from which a Markovian forecasting model is developed to aid policymakers. Our approach applies to any event-based database like GTD. Finally, the caterpillar diagram is a domain-independent framework that can visualize variations in any univariate data series, thereby assisting in system monitoring.
一种创新的恐怖主义威胁预警系统颜色编码方案
这项研究开发了一个创新的恐怖威胁咨询系统,能够向决策者或公众直观地传达恐怖主义水平的变化,并预测未来的水平。由于对该系统的信任不足,政策制定者早些时候创建类似咨询系统的尝试要么停止,要么失去了相关性。我们提出了一种创建配色方案的新方法,并利用它来开发一个直观的毛虫图,总结恐怖主义的各个阶段。它使用全球恐怖主义数据库(GTD)纳入了一个国家或地区的全球恐怖主义影响评分。此外,连续周期之间的毛虫图中的颜色转换模拟了马尔可夫过程,从而使我们能够开发预测模型。我们成功地证明了所提出的毛毛虫图和预测模型对印度、伊拉克及其各自地区的有效性。预测模型表明,在这些国家及其地区,红色所描绘的侵略性恐怖主义阶段以及上升(黄色)和下降(青色)的短暂阶段是最有可能的。所提出的毛虫图是一种识别恐怖主义模式的创新可视化方法,从中开发了一个马尔可夫预测模型来帮助决策者。我们的方法适用于任何基于事件的数据库,如GTD。最后,卡特彼勒图是一个独立于领域的框架,可以可视化任何单变量数据序列中的变化,从而有助于系统监控。
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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来源期刊
Methodological Innovations
Methodological Innovations Social Sciences-Sociology and Political Science
CiteScore
3.30
自引率
0.00%
发文量
31
审稿时长
15 weeks
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