Suchergebnisse

Using data that combines information from the Federal Aviation Administration, the RAND Corporation and a newly developed database on global terrorist activity, we are able to examine trends in 1,101 attempted aerial hijackings that occurred around the world from 1931 to 2003. We have especially complete information for 828 hijackings that occurred before 1986. Using a rational choice theoretical framework, we use continuous‐time survival analysis to estimate the impact of several major counterhijacking interventions on the hazard of differently motivated hijacking attempts and logistic regression analysis to model the predictors of successful hijackings. Some of these interventions use certainty‐based strategies of target hardening to reduce the perceived likelihood of success. Others focus on raising the perceived costs of hijacking by increasing the severity of punishment. We also assess which strategies were most effective in deterring hijackers whose major purpose was related to terrorism. We found support for the conclusion that new hijacking attempts were less likely to be undertaken when the certainty of apprehension was increased through metal detectors and law enforcement at passenger checkpoints. We also found that fewer hijackers attempted to divert airliners to Cuba once that country made it a crime to hijack flights. Our results support the contagion view that hijacking rates significantly increase after a series of hijackings closely clustered in time—but only when these attempts were successful. Finally, we found that the policy interventions examined here significantly decreased the likelihood of nonterrorist but not that of terrorist hijackings.

Why did some American citizens choose to travel to fight in Syria and Iraq rather than engage in Islamic State of Iraq and Syria (ISIS)-inspired terrorism in the United States? We conducted a social network analysis (SNA) on a sample (n = 224) of extremists who either plotted ISIS-inspired attacks within the United States or attempted to travel to Syria or Iraq to join the group between 2013-2020. We test how network size, network interconnectedness, and the importance of trusted network members impact the choice of American ISIS offenders to travel or plot terrorist attacks. Our results show that Americans were more likely to choose to travel to fight when they had access to large, dense networks that were embedded with trusted associates. Those without access to similar networks abandoned their preferences for foreign fighting and instead plotted attacks within the United States. The findings provide pertinent policy implications for countering violent extremism.

Why did some American citizens choose to travel to fight in Syria and Iraq rather than engage in Islamic State of Iraq and Syria (ISIS)-inspired terrorism in the United States? We conducted a social network analysis (SNA) on a sample ( n = 224) of extremists who either plotted ISIS-inspired attacks within the United States or attempted to travel to Syria or Iraq to join the group between 2013-2020. We test how network size, network interconnectedness, and the importance of trusted network members impact the choice of American ISIS offenders to travel or plot terrorist attacks. Our results show that Americans were more likely to choose to travel to fight when they had access to large, dense networks that were embedded with trusted associates. Those without access to similar networks abandoned their preferences for foreign fighting and instead plotted attacks within the United States. The findings provide pertinent policy implications for countering violent extremism.

Abstract
Background
Crime, traffic accidents, terrorist attacks, and other space-time random events are unevenly distributed in space and time. In the case of crime, hotspot and other proactive policing programs aim to focus limited resources at the highest risk crime and social harm hotspots in a city. A crucial step in the implementation of these strategies is the construction of scoring models used to rank spatial hotspots. While these methods are evaluated by area normalized Recall@k (called the predictive accuracy index), models are typically trained via maximum likelihood or rules of thumb that may not prioritize model accuracy in the top k hotspots. Furthermore, current algorithms are defined on fixed grids that fail to capture risk patterns occurring in neighborhoods and on road networks with complex geometries.

Results
We introduce CrimeRank, a learning to rank boosting algorithm for determining a crime hotspot map that directly optimizes the percentage of crime captured by the top ranked hotspots. The method employs a floating grid combined with a greedy hotspot selection algorithm for accurately capturing spatial risk in complex geometries. We illustrate the performance using crime and traffic incident data provided by the Indianapolis Metropolitan Police Department, IED attacks in Iraq, and data from the 2017 NIJ Real-time crime forecasting challenge.

Conclusion
Our learning to rank strategy was the top performing solution (PAI metric) in the 2017 challenge. We show that CrimeRank achieves even greater gains when the competition rules are relaxed by removing the constraint that grid cells be a regular tessellation.

AbstractAlthough research on terrorism has grown rapidly in recent years, few scholars have applied criminological theories to the analysis of individual‐level political extremism. Instead, researchers focused on radicalization have drawn primarily from political science and psychology and have overwhelmingly concentrated on violent extremists, leaving little variation in the dependent variable. With the use of a newly available data set, we test whether variables derived from prominent criminological theories are helpful in distinguishing between nonviolent and violent extremists. The results show that variables related to social control (lack of stable employment), social learning (radical peers), psychological perspectives (history of mental illness), and criminal record all have significant effects on participation in violent political extremism and are robust across multiple techniques for imputing missing data. At the same time, other common indicators of social control (e.g., education and marital status) and social learning perspectives (e.g., radical family members) were not significant in the multivariate models. We argue that terrorism research would benefit from including criminology insights and by considering political radicalization as a dynamic, evolving process, much as life‐course criminology treats more common forms of crime.

Introduction -- Networks-plus: beyond the individual (teams and contexts) -- Networks-plus: within the individual -- Multilevel, high-dimensional, evolving, and emerging networks -- Discussion -- Appendixes: A. Statement of task for the decadal survey of social and behavioral sciences for applications to national security; B. Workshop agenda; C. Participants list; D. Biographical sketches of steering committee members and presenters.