Near-repeat terrorism: Identifying and analyzing the spatiotemporal attack patterns of major terrorist organizations

Abstract

For many decades, the contagion of terrorism has presented a huge risk to our global society. To this end, previous research has found that single terrorist attacks can elevate the risk of subsequent attacks nearby, an idea referred to as the near-repeat phenomenon. A near-repeat pair consists of two attacks that occur within a specific time period and spatial distance of one another (e.g, one week and 10 miles), and the existence of near-repeats reflects calculated decisions by terrorists as they plan when and where to attack. Thus, enhancing our understanding of these attack patterns can shed light into the operational strategies of terrorist organizations. To this end, there remains key gaps in current knowledge regarding whether near-repeat attack patterns generalize across major terrorist organizations (i.e., do all major organizations exhibit near-repeat activity?), and the major risk factors associated with near-repeat terrorism (e.g., attack tactics). Utilizing data on over 50,000 terrorist attacks, this study seeks to fill these gaps in knowledge by first analyzing near-repeat attack patterns both across and within major terrorist organizations, and subsequently developing a statistical learning pipeline to identify the risk factors which are most salient in near-repeat attacks. We find that near-repeat terrorism occurs at a statistically significant level for 28 out of the 30 organizations studied. Although our findings show that near-repeat attacks are common amongst organizations, we find that the tactics (e.g., weapon choice, target type) utilized within near-repeat attacks vary vastly between organizations. The results of this work offer insights that augment our knowledge of terrorism patterns, which can in turn improve counterterrorism operations. Further, our end-to-end data-driven framework offers a strong decision support tool in which users can first detect near-repeat attacks, and subsequently identify the key operational patterns within those attacks (for any terrorist organizations of interest).