scholarly journals Study on Correlation Factors that Influence Terrorist Attack Fatalities Using Global Terrorism Database

2014 ◽  
Vol 84 ◽  
pp. 698-707 ◽  
Author(s):  
Li Guohui ◽  
Lu Song ◽  
Cheng Xudong ◽  
Yang Hui ◽  
Zhang Heping
Keyword(s):  
Terrorist Attack ◽  
Global Terrorism ◽  
Global Terrorism Database ◽  
Correlation Factors

scholarly journals Quantitative Research on Global Terrorist Attacks and Terrorist Attack Classification

2019 ◽  
Vol 11 (5) ◽  
pp. 1487 ◽  
Author(s):  
Xueli Hu ◽  
Fujun Lai ◽  
Gufan Chen ◽  
Rongcheng Zou ◽  
Qingxiang Feng
Keyword(s):  
Quantitative Research ◽  
Terrorist Attack ◽  
Relevant Literature ◽  
Network Models ◽  
Terrorist Attacks ◽  
Terrorist Organizations ◽  
Terrorist Organization ◽  
Global Terrorism ◽  
The Impact ◽  
Global Terrorism Database

Terrorist attacks are events which hinder the development of a region. Before the terrorist attacks, we need to conduct a graded evaluation of the terrorist attacks. After getting the level of terrorist attacks, we can fight terrorist organizations more effectively. This paper builds rating models for terrorist attacks, hidden or emerging terrorist organization classification discovery models, terrorist organization alliance network models and more, through quantitative research of the Global Terrorism Database, which solved the event classification. Through studying relevant literature and the variables of the Global Terrorism Database, this paper sorted out 25 observation variables related to the impact level (level of harm) of terrorist attacks. By establishing a mathematical model of factor analysis, 11 factors related to the impact level (level of harm) of terrorist attacks were constructed, and the variance of the contribution of each factor was used as the weight to calculate the comprehensive rate of the impact level of each terrorist attack. Finally, K-means clustering method is used to cluster and analyze the comprehensive rate of impact level, and the top 10 terrorist attacks with the highest impact level in the past two decades were obtained.

scholarly journals Quantitative Analysis of Global Terrorist Attacks Based on the Global Terrorism Database

2021 ◽  
Vol 13 (14) ◽  
pp. 7598
Author(s):  
Zhongbei Li ◽  
Xiangchun Li ◽  
Chen Dong ◽  
Fanfan Guo ◽  
Fan Zhang ◽  
...  
Keyword(s):  
Southeast Asia ◽  
Terrorist Attack ◽  
Risk Index ◽  
Three Dimensions ◽  
Terrorist Attacks ◽  
Analytic Hierarchy ◽  
The Past ◽  
Global Terrorism ◽  
The Government ◽  
Global Terrorism Database

Terrorist attacks have become a serious source of risk affecting the security of the international community. Using the Global Terrorism Database (GTD), in order to quantitatively study past terrorist attacks and their temporal and spatial evolution the analytic hierarchy process (AHP) was used to classify the degree of damage from terrorist attacks. The various factors influencing terrorist attacks were extracted and represented in three dimensions. Subsequently, using MATLAB for analysis and processing, the grading standards for terrorist attacks were classified into five levels according to the degree of hazard. Based on this grading standard, the top ten terrorist attacks with the highest degree of hazard in the past two decades were listed. Because the characteristics and habits of a terrorist or group exhibit a certain consistency, the K-means cluster analysis method was used to classify terrorists according to region, type of attack, type of target and type of weapon used by the terrorists. Several attacks that might have been committed by the same terrorist organization or individual at different times and in different locations were classified into one category, and the top five categories were selected according to the degree of sabotage inflicted by the organization or individual. Finally, the spatiotemporal evolution of terrorist attacks in the past three years was analyzed, considering the terrorist attack targets and key areas of terrorist attacks. The Middle East, Southeast Asia, Central Asia, and Africa were predicted to be the regions that will be most seriously affected by future global terrorist events. The terrorist attacks in Southeast Asia are expected to become more severe, and the scope of terrorist attacks in Africa is expected to widen. Civilians are the targets most at risk for terrorist attacks, and the corresponding risk index is considerably higher than it is for other targets. The results of this research can help individuals and the government to enable a better understanding of terrorism, improve awareness to prevent terrorism and enhance emergency management and rescue, and provide a solid and reliable basis and reference for joint counterterrorism in various countries and regions.

scholarly journals Using Global Terrorism Database (GTD) and Machine Learning Algorithms to Predict Terrorism and Threat

2019 ◽  
Vol 9 (1) ◽  
pp. 5995-6000 ◽  
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Intelligent System ◽  
Machine Learning Algorithms ◽  
Internet Technology ◽  
Social Media Platforms ◽  
Future Events ◽  
Global Terrorism ◽  
Terrorist Event ◽  
Global Terrorism Database

It is evident that there has been enormous growth in terrorist attacks in recent years. The idea of online terrorism has also been growing its roots in the internet world. These types of activities have been growing along with the growth in internet technology. These types of events include social media threats such as hate speeches and comments provoking terror on social media platforms such as twitter, Facebook, etc. These activities must be prevented before it makes an impact. In this paper, we will make various classifiers that will group and predict various terrorism activities using k-NN algorithm and random forest algorithm. The purpose of this project is to use Global Terrorism Database as a dataset to detect terrorism. We will be using GTD which stands for Global Terrorism Database which is a publicly available database which contains information on terrorist event far and wide from 1970 through 2017 to train a machine learning-based intelligent system to predict any future events that could bring threat to the society.

scholarly journals Local alliances and rivalries shape near-repeat terror activity of al-Qaeda, ISIS, and insurgents

2019 ◽  
Vol 116 (42) ◽  
pp. 20898-20903 ◽  
Author(s):  
Yao-Li Chuang ◽  
Noam Ben-Asher ◽  
Maria R. D’Orsogna
Keyword(s):  
Policy Making ◽  
Spillover Effects ◽  
Terrorist Attacks ◽  
Al Qaeda ◽  
Islamic State ◽  
Collaborative Relationship ◽  
Regional Dynamics ◽  
Global Terrorism ◽  
Near Repeat ◽  
Global Terrorism Database

We study the spatiotemporal correlation of terrorist attacks by al-Qaeda, the Islamic State of Iraq and Syria (ISIS), and local insurgents, in six geographical areas identified via k-means clustering applied to the Global Terrorism Database. All surveyed organizations exhibit near-repeat activity whereby a prior attack increases the likelihood of a subsequent one by the same group within 20 km and on average 4 (al-Qaeda) to 10 (ISIS) weeks. Near-response activity, whereby an attack by a given organization elicits further attacks from a different one, is found to depend on the adversarial, neutral, or collaborative relationship between the two. When in conflict, local insurgents respond quickly to attacks by global terror groups while global terror groups delay their responses to local insurgents, leading to an asymmetric dynamic. When neutral or allied, attacks by one group enhance the response likelihood of the other, regardless of hierarchy. These trends arise consistently in all clusters for which data are available. Government intervention and spillover effects are also discussed; we find no evidence of outbidding. Understanding the regional dynamics of terrorism may be greatly beneficial in policy making and intervention design.

Terrorist Attacks Targeting Police, 1998–2010: Exploring Heavily Hit Countries

2018 ◽  
Vol 30 (3) ◽  
pp. 261-278
Author(s):  
Jennifer C. Gibbs
Keyword(s):  
Law Enforcement ◽  
Terrorist Attacks ◽  
Future Research ◽  
Common Thread ◽  
Global Terrorism ◽  
The Government ◽  
Global Terrorism Database ◽  
Scholarly Attention

With over 14% of all terrorist attacks since 1970 targeting law enforcement, terrorist attacks on police is a problem in need of scholarly attention. Police serve as symbolic targets of the government and strategic targets of terrorist attacks, yet we know little about such attacks. This article explores terrorist attacks targeting police in heavily hit countries, drawing from the Global Terrorism Database. While Iraq and India have the most terrorist attacks targeting police, these countries also have a high number of terrorist attacks against all targets. To account for the total number of terrorist attacks, proportions are explored, finding Macedonia, Russia, and Georgia have the highest proportions of terrorist attacks targeting police between 1998 and 2010. A common thread among these heavily hit countries is a rapidly changing governing regime coupled with societal schism—in other words, these countries seem to share low governmental legitimacy. Implications for future research are discussed.

The Effect of Terrorism on Judicial Confidence

2017 ◽  
Vol 70 (4) ◽  
pp. 790-802
Author(s):  
Steven V. Miller
Keyword(s):  
Due Process ◽  
Judicial Independence ◽  
Mixed Effects ◽  
Mixed Effects Models ◽  
Negative Effects ◽  
Security Dilemma ◽  
European Values Survey ◽  
European Values ◽  
Global Terrorism ◽  
Global Terrorism Database

Independent judiciaries prevent democratic reversals, facilitate peaceful transitions of power, and legitimate democracy among citizens. We believe this judicial independence is important for citizen-level judicial confidence and faith in democratic institutions. I challenge this and argue that citizens living under terror threats lose confidence in their independent judiciaries. Terror threats lead citizens to enable the state leader to provide counterterrorism for their security, which has important implications for interbranch relations between the executive and the judiciary. Citizens lose confidence in independent judiciaries that provide due process for suspected terrorists. I test my argument with mixed effects models that incorporate the Global Terrorism Database and four waves of European Values Survey. The analyses demonstrate the negative effects of terror threats on judicial confidence when interacting terror threats with measures of judicial independence. My findings have important implications for the study of democratic confidence and the liberty-security dilemma.

There Can Be No Compromise: Institutional Inclusiveness, Fractionalization and Domestic Terrorism

2012 ◽  
Vol 43 (3) ◽  
pp. 541-557 ◽  
Author(s):  
Dennis M. Foster ◽  
Alex Braithwaite ◽  
David Sobek
Keyword(s):  
Civil War ◽  
Minority Groups ◽  
Proportional Representation ◽  
Social Mobilization ◽  
Domestic Terrorism ◽  
Terrorist Attacks ◽  
Small Minority ◽  
Political Actors ◽  
Global Terrorism ◽  
Global Terrorism Database

Research on terrorism in democracies borrows from the literature on civil war and rebellion to argue that more proportional representation decreases the likelihood of terrorist violence. However, theories of broader social mobilization may be ill-suited to predicting the occurrence of terrorism. This article proposes that proportionalism's institutionalization of small minority groups as legitimate but relatively insignificant political actors leads to militancy. Analyses of the Global Terrorism Database on domestic terrorist attacks across all democracies in 1975–2007 provide broad support for this argument. The presence and greater degrees of proportionalism are significantly associated with greater levels of domestic terrorism when ethnic fractionalization within a given society increases. Moreover, domestic terrorism increases as the number of small parties represented in the legislature increases.

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