Public Discourse & Trust Modeling
MerckModeled how themes, events, reach, and timing shaped public sentiment and Trust in a complex media environment.
Challenge
A global healthcare company needed a data-driven view of how media themes, events, and public discourse influenced vaccine sentiment. The goal was to identify communication watchouts, Trust-building opportunities, and moments where proactive storytelling could shape the narrative.
Approach
Used predictive AI and statistical modeling to evaluate how selected topics and events influenced discourse over time. The model separated baseline sentiment from topic-driven swings and measured Trust-driving and distrust-driving mentions separately before calculating net discourse impact.
Impact
The work showed that media volume alone did not explain impact. Reach, timing, topic alignment, and sentiment dynamics mattered. Confidence-oriented conversations reached four times as many people, while negative sentiment tended to peak up to five days after positive sentiment. That timing created an opportunity for more proactive narrative planning.
Selected slides
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