Abstract
Social Science Future attacks by terrorist organizations are difficult to predict because their organizational capabilities and resources are hidden. Yang et al. developed a modeling approach for estimating these parameters to predict future terror attacks. By testing their model against the Global Terrorism Database, they could explain about 60% of the variance in a terrorist group's future lethality using only its first 10 to 20 attacks, outperforming previous models. The model also captures the dynamics by which terror organizations shift from random, low-fatality attacks to nonrandom, high-fatality attacks. These results have implications for efforts to combat terrorism worldwide. Proc. Natl. Acad. Sci. U.S.A. 116 , 21463 (2019).
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