Foreign media reports pose a national security issue when they are empirically linked to crisis timing, domestic bridge circulation, platform amplification and institutional vulnerability. Developing a defence empirical framework to measure the level of coupling in protest-friendly political Windows. Constructs a public-domain corpus using GDELT 2.0 news records, Media Cloud source lists, ACLED protest and political-violence event metadata, and manually verifies the public repost observation. The final corpus contains 18 event windows from 2014 to 2024, 234 weekly observations, 62,418 raw news-mention records, 8,724 deduplicated media items, 31,506 public repost observations, and 2,184 elite or external institutional statements. Each week’s content category code with 7 international media tactics and the six platformsignal families; Then link institutional trust vulnerability and response capability variables. Through the estimation of narrative-platform coupling using semantic similarity, tactic-distribution correlation, source linkage, bridge reposting, elite-message incorporation, and temporal memory. Validates using the leave-one-window-out method, sets aside 5 reduced bases, conducts perturbation tests, etc. The empirical evidence shows that the source of disintegration is primarily in Interaction Zone rather than foreign-introduced reporting. The strength of coupling between grievance amplification and sentiment volatility is 0.88, while that between external verification and cross-media synchronization is 0.87; The degree of narrative saturation increased from 31 to 84 on the 0-100 scale around the triggering period; Domestic Bridge reposting reached 83 one week later, still high after Foreign Synchronization dropped. The full model achieves an early warning F1 of 0.842; Scenario AUC is 0.901; Calibration Score is 0.873; The Median Lead Time is 8.4 days. Removing institutional trust results in the greatest calibration error; The text-only baseline obtains a score of F1=0.711. Countermeasures simulation show that the balanced Package, which includes provenance disclosure, fast correction, transparent labelling, civic pre-bunking and limited platform coordination, reduces modelled risk by 34.7 per cent with a civil-liberty cost index of 0.21. The study also reports case-type error profiles: election-dispute windows have the lowest median prediction error at 4.5 percentage points, while security-incident windows have the highest at 8.3 points because public evidence is delayed and visual material spreads before verification. The above-mentioned results define this model as an analyst-review aid but not an automatic-enforcement device. The results support an outward bound country-wide safeguard based on attribution from evidence to information transparency with judicial oversight of platforms’ cooperative agreements. The Corpus-based test shows that with the addition of warnings about source-cluster provenance, bridge-path evidence and case-type errors estimated in this manner become progressively credible. Keeping it empirically usable in a reviewer’s hands instead of being forced into an automatic rule-breaker.
