A normative approach to radicalization in social networks

In recent decades, the massification of online social connections has made information globally accessible in a matter of seconds. Unfortunately, this has been accompanied by a dramatic surge in extreme opinions, without a clear solution in sight. Using a model performing probabilistic inference in large-scale loopy graphs through exchange of messages between nodes, we show how circularity in the social graph directly leads to radicalization and the polarization of opinions. We demonstrate that these detrimental effects could be avoided by actively decorrelating the messages in social media feeds. This approach is based on an extension of Belief Propagation (BP) named Circular Belief Propagation (CBP) that can be trained to drastically improve inference within a cyclic graph. CBP was benchmarked using data from Facebook and Twitter. This approach could inspire new methods for preventing the viral spreading and amplification of misinformation online, improving the capacity of social networks to share knowledge globally without resorting to censorship.Comment: 23 pages, 8 figures, 1 supplementary materia

Assimilation multi-échelle dans un modèle météorologique régional

TOULOUSE3-BU Sciences (315552104) / SudocSudocFranceF

From hallucinations to synaesthesia: A circular inference account of unimodal and multimodal erroneous percepts in clinical and drug-induced psychosis

International audiencePsychedelics distort perception and induce visual and multimodal hallucinations as well as synaesthesia. This is in contradiction with the high prevalence of distressing voices in schizophrenia. Here we introduce a unifying account of unimodal and multimodal erroneous percepts based on circular inference. We show that amplification of top-down predictions (descending loops) leads to an excessive reliance on priors and aberrant levels of integration of the sensory representations, resulting in crossmodal percepts and stronger illusions. By contrast, amplification of bottom-up information (ascending loops) results in overinterpretation of unreliable sensory inputs and high levels of segregation between sensory modalities, bringing about unimodal hallucinations and reduced vulnerability to illusions. We delineate a canonical microcircuit in which layer-specific inhibition controls the propagation of information across hierarchical levels: inhibitory interneurons in the deep layers exert control over priors, removing descending loops. Conversely, inhibition in the supragranular layers counterbalances the effects of the ascending loops. Overall, we put forward a multiscale and transnosographic account of erroneous percepts with important theoretical, conceptual and clinical implications

Hydro-meteorological evaluation of a convection-permitting ensemble prediction system for Mediterranean heavy precipitating events

International audienceAn assessment of the performance of different convection-permitting ensemble prediction systems (EPSs) is performed, with a focus on Heavy Precipitating Events (HPEs). The convective-scale EPS configuration includes perturbations of lateral boundary conditions (LBCs) by using a global ensemble to provide LBCs, initial conditions (ICs) through an ensemble data assimilation technique and perturbations of microphysical parameterisations to account for part of model errors. A probabilistic evaluation is conducted over an 18-day period. A clear improvement is found when uncertainties on LBCs and ICs are considered together, but the chosen microphysical perturbations have no significant impact on probabilistic scores. Innovative evaluation processes for three HPE case studies are implemented. First, maxima diagrams provide a multiscale analysis of intense rainfall. Second, an hydrological evaluation is performed through the computation of discharge forecasts using hourly ensemble precipitation forecasts as an input. All ensembles behave similarly, but differences are found highlighting the impact of microphysical perturbations on HPEs forecasts, especially for cases involving complex small-scale processes

Conspiracy beliefs and perceptual inference in times of political uncertainty

Socio-political crises with uncertain issues accumulated in recent years, providing fertile ground for the emergence of conspiracy ideations. Computational models constitute valuable tools for understanding the mechanisms at play in the formation and rigidification of these unshakeable beliefs. Here, the Circular Inference model was used to capture associations between changes in perceptual inference, and the dynamics of conspiracy ideations in times of uncertainty. Large populations from three polarized countries performed a bistable perception task and conspiracy beliefs assessments, around major socio-political events. We show that when uncertainty peaks, an overweighting of sensory information is associated with conspiracy ideations. Progressively, this exploration strategy gives way to an exploitation strategy, in which increased adherence to conspiracy theories is associated with the amplification of prior information. Overall, the Circular Inference model sheds new light on the possible mechanisms underlying the progressive rigidification of conspiracy theories when facing highly uncertain situations

Conspiracy beliefs and perceptual inference in times of political uncertainty.

International audienceSociopolitical crises causing uncertainty have accumulated in recent years, providing fertile ground for the emergence of conspiracy ideations. Computational models constitute valuable tools for understanding the mechanisms at play in the formation and rigidification of these unshakeable beliefs. Here, the Circular Inference model was used to capture associations between changes in perceptual inference and the dynamics of conspiracy ideations in times of uncertainty. A bistable perception task and conspiracy belief assessment focused on major sociopolitical events were administered to large populations from three polarized countries. We show that when uncertainty peaks, an overweighting of sensory information is associated with conspiracy ideations. Progressively, this exploration strategy gives way to an exploitation strategy in which increased adherence to conspiracy theories is associated with the amplification of prior information. Overall, the Circular Inference model sheds new light on the possible mechanisms underlying the progressive strengthening of conspiracy theories when individuals face highly uncertain situations