01Attributes narrative effects to specific actors via doubly-robust causal inference with Rosenbaum sensitivity analysis.
02Models belief propagation using DeGroot social learning on influence networks, returning polarization index and belief cluster structure.
03Optimizes counter-narrative strategy through Bayesian Stackelberg game theory, providing optimal intervention actions and timing alarms.
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05Detects coordinated narrative operations via coupled SIR-Hawkes epidemiological model with threat levels (LOW/MEDIUM/HIGH/CRITICAL).
06Maps influence network topology using submodular greedy influence maximization and persistent homology to identify echo chambers and fragmentation.
