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Register a new userGender-specific behavior change following terror attacks
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Terrorists use violence in pursuit of political goals. While terror often has severe consequences for victims, it remains an open question how terror attacks affect the general population. We study the behavioral response of citizens of cities affected by $7$ different terror attacks. We compare real-time mobile communication patterns in the first $24$ hours following a terror attack to the corresponding patterns on days with no terror attack. On ordinary days, the group of female and male participants have different activity patterns. Following a terror attack, however, we observe a significant increase of the gender differences. Knowledge about citizens behavior response patterns following terror attacks may have important implications for the public response during and after an attack.
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We study the spatiotemporal correlation of terrorist attacks by al-Qaeda, 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 20km 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 is available. Government intervention and spill-over 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.
We study the dynamic network of relationships among avatars in the massively multiplayer online game Planetside 2. In the spring of 2014, two separate servers of this game were merged, and as a result, two previously distinct networks were combined into one. We observed the evolution of this network in the seven month period following the merger and report our observations. We found that some structures of original networks persist in the combined network for a long time after the merger. As the original avatars are gradually removed, these structures slowly dissolve, but they remain observable for a surprisingly long time. We present a number of visualizations illustrating the post-merger dynamics and discuss time evolution of selected quantities characterizing the topology of the network.
Public stakeholders implement several policies and regulations to tackle gender gaps, fostering the change in the cultural constructs associated with gender. One way to quantify if such changes elicit gender equality is by studying mobility. In this work, we study the daily mobility patterns of women and men occurring in Medellin (Colombia) in two years: 2005 and 2017. Specifically, we focus on the spatiotemporal differences in the travels and find that purpose of travel and occupation characterise each gender differently. We show that women tend to make shorter trips, corroborating Ravensteins Laws of Migration. Our results indicate that urban mobility in Colombia seems to behave in agreement with the archetypal case studied by Ravenstein.
Disinformation continues to attract attention due to its increasing threat to society. Nevertheless, a disinformation-based attack on critical infrastructure has never been studied to date. Here, we consider traffic networks and focus on fake information that manipulates drivers decisions to create congestion. We study the optimization problem faced by the adversary when choosing which streets to target to maximize disruption. We prove that finding an optimal solution is computationally intractable, implying that the adversary has no choice but to settle for suboptimal heuristics. We analyze one such heuristic, and compare the cases when targets are spread across the city of Chicago vs. concentrated in its business district. Surprisingly, the latter results in more far-reaching disruption, with its impact felt as far as 2 kilometers from the closest target. Our findings demonstrate that vulnerabilities in critical infrastructure may arise not only from hardware and software, but also from behavioral manipulation.
Empirical estimation of critical points at which complex systems abruptly flip from one state to another is among the remaining challenges in network science. However, due to the stochastic nature of critical transitions it is widely believed that critical points are difficult to estimate, and it is even more difficult, if not impossible, to predict the time such transitions occur [1-4]. We analyze a class of decaying dynamical networks experiencing persistent attacks in which the magnitude of the attack is quantified by the probability of an internal failure, and there is some chance that an internal failure will be permanent. When the fraction of active neighbors declines to a critical threshold, cascading failures trigger a network breakdown. For this class of network we find both numerically and analytically that the time to the network breakdown, equivalent to the network lifetime, is inversely dependent upon the magnitude of the attack and logarithmically dependent on the threshold. We analyze how permanent attacks affect dynamical network robustness and use the network lifetime as a measure of dynamical network robustness offering new methodological insight into system dynamics.
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