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Abstract Public sentiment towards the police is a matter of great interest in the United States, as reports on police misconduct are increasingly being published in mass and social media. Here, we test how the public’s perception of the police can be majorly shaped by media reports of police brutality and local crime. We collect data on media coverage of police brutality and local crime, together with Twitter posts from 2010-2020 about the police in 18 metropolitan areas in the country. Using a range of model-free approaches building on transfer entropy analysis, we discover an association between public sentiment towards the police and media coverage of police brutality. We cautiously interpret this relationship as causal. Through this lens, the public’s sentiment towards the police appears to be driven by media-projected images of police misconduct, with no statistically significant evidence for a comparable effect driven by media reports on crimes. 

Abstract Transfer entropy is emerging as the statistical approach of choice to support the inference of causal interactions in complex systems from time-series of their individual units. With reference to a simple dyadic system composed of two coupled units, the successful application of net transfer entropy-based inference relies on unidirectional coupling between the units and their homogeneous dynamics. What happens when the units are bidirectionally coupled and have different dynamics? Through analytical and numerical insights, we show that net transfer entropy may lead to erroneous inference of the dominant direction of influence that stems from its dependence on the units’ individual dynamics. To control for these confounding effects, one should incorporate further knowledge about the units’ time-histories through the recent framework offered by momentary information transfer. In this realm, we demonstrate the use of two measures: controlled and fully controlled transfer entropies, which consistently yield the correct direction of dominant coupling irrespective of the sources and targets individual dynamics. Through the study of two real-world examples, we identify critical limitations with respect to the use of net transfer entropy in the inference of causal mechanisms that warrant prudence by the community. 

The phenomenon of fish schooling - coordinated swimming of fish in polarized groups of specific spatial formations- is commonly observed in several species of fish. Fish schooling may even provide hydrodynamic advantages reducing the overall swimming cost of the group. To date, the role of hydrodynamics in coordinated swimming is not completely understood as it is difficult to separately study the role of hydrodynamic interaction from other forms of interaction between the fish. Here, we propose a statistical methodology based on information theoretic tools and flow velocity measurements, that can potentially tease out the hydrodynamic interaction pathways from visual and tactile ones. To avoid experimental confounds from bidirectional interactions and objectively understand cause-and-effect relationships, we design a robotic platform that mimics the behavior of two fish swimming in-line in a controlled setup inside a water channel. We examine the response of a flag to the fish-like unsteady wake generated by an actively pitching airfoil located upstream. We systematically quantify the passive hydrodynamic effect by studying the flapping motion of the flag located downstream of the airfoil in response to both periodic pitching and less predictable, random startling motion of the upstream airfoil. The study integrates experimental biomimetics with information theory to establish a deeper understanding of hydrodynamics in fish schooling. 

Fish often swim in crystallized group formations (schooling) and orient themselves against the incoming flow (rheotaxis). At the intersection of these two phenomena, we investigate the emergence of unique schooling patterns through passive hydrodynamic mechanisms in a fish pair, the simplest subsystem of a school. First, we develop a fluid dynamics-based mathematical model for the positions and orientations of two fish swimming against a flow in an infinite channel, modelling the effect of the self-propelling motion of each fish as a point-dipole. The resulting system of equations is studied to gain an understanding of the properties of the dynamical system, its equilibria and their stability. The system is found to have five types of equilibria, out of which only upstream swimming in in-line and staggered formations can be stable. A stable near-wall configuration is observed only in limiting cases. It is shown that the stability of these equilibria depends on the flow curvature and streamwise interfish distance, below critical values of which, the system may not have a stable equilibrium. The study reveals that simply through passive fluid dynamics, in the absence of any other feedback/sensing, we can justify rheotaxis and the existence of stable in-line and staggered schooling configurations.