Incident brief
Timeline, known facts, unresolved claims, involved parties, and the response already planned.
Public pressure simulation
Public Opinion Simulation AI
Simulate how media, institutions, affected groups, and online audiences may react to an incident, policy, announcement, or crisis before the narrative hardens.
Built for scenario planning, not certainty. Every output should be reviewed against real evidence before an operating decision.
Scenario tape / illustrative
Public reaction simulation for a policy announcement
R1
Affected groupFairness concern appears
R2
Media accountsConflict frame spreads
R3
InstitutionsTrust response becomes decisive
Dominant risk
Trust erosion
Amplifier
Conflict frame
Evidence gap
Affected-group motive
Input
Incident, policy, statement, public source
Engine
Stakeholder graph + narrative rounds
Output
Escalation risks and response gaps
What to bring
Bring the material that defines the public question.
Public opinion simulation works best when the source includes the event, affected groups, institutional constraints, and the message people will judge.
Policy or announcement
Draft language, target audience, expected benefits, likely objections, and institutional constraints.
Media and public context
Articles, comments, public posts, prior controversies, or community concerns that shape interpretation.
Where it earns its keep
Find the reaction path before it becomes the public story.
The first official explanation is rarely the only story. MiroFish helps teams inspect how competing narratives may move between people, platforms, and institutions.
Incident response01
See which question the public will ask first.
Test whether the reaction centers on harm, responsibility, fairness, competence, or trust.
Policy pressure02
Identify who feels the cost before launch.
Simulate how groups with different incentives interpret the same policy or governance change.
Crisis messaging03
Pressure-test the response before time pressure hits.
Surface weak language, missing evidence, and likely escalation points in a planned statement.
Public opinion is a system of interpretation.
MiroFish treats the event as a world of actors and memory, not a sentiment score. The useful question is how interpretation changes across rounds.
Stage 1
Ground the scenario
Upload source material and define the decision, event, or message you want to test.
Stage 2
Build the actor graph
Map the people, groups, incentives, constraints, and memory that shape the reaction.
Stage 3
Run reaction rounds
Let the simulated actors respond over multiple rounds so the second-order path appears.
Stage 4
Question the report
Review the trajectory, risks, weak assumptions, and what evidence would change the conclusion.
What the report should answer
The report should expose the pressure structure.
- Which narrative forms first and why
- Which actor can amplify or calm the reaction
- Where the official message may be misunderstood
- What evidence would reduce uncertainty
- What response question to ask next
Boundary conditions
Not a replacement for judgment or live monitoring.
- Not guaranteed public sentiment prediction
- Not a substitute for legal, policy, or communications review
- Not live social listening unless current sources are provided
- Not useful when the source material hides critical facts
Why MiroFish
A useful public opinion forecast needs visible actors.
Generic AI can summarize a likely reaction. MiroFish shows the actor graph and reaction rounds so the team can inspect the path.
Reaction model
Generic AI
One likely summary
MiroFish
Stakeholder paths over multiple rounds
Risk surface
Generic AI
General advice
MiroFish
Escalation points, amplifiers, and response gaps
Review loop
Generic AI
Ask again from scratch
MiroFish
Question the simulated report and its assumptions
FAQ
Public opinion simulation AI, without the guesswork.
The goal is not certainty. The goal is to expose the reaction path early enough to improve the decision.
What is public opinion simulation AI?+
Public opinion simulation AI explores how different groups may interpret and react to an incident, announcement, policy, or crisis. MiroFish does this by building an actor graph and running multi-round reactions from the evidence you provide.
Can it predict exact public sentiment?+
No. MiroFish is for scenario analysis, not exact sentiment polling. It helps identify plausible narratives, amplifiers, escalation risks, and missing evidence.
What inputs work best?+
Useful inputs include incident timelines, draft statements, policy documents, media articles, public comments, research notes, and prior context around the affected groups.
How is this different from social listening?+
Social listening observes signals that already exist. MiroFish helps rehearse how a scenario may unfold before or alongside those signals, depending on the evidence you provide.
Who should use it?+
Communications teams, policy teams, founders, researchers, and operators can use it before publishing a statement, launching a policy, or responding to a sensitive event.
Related simulation paths
Follow the risk into the next decision.
Most decisions do not stay inside one category. These adjacent use cases help teams test the next market, customer, or public reaction path.
Sentiment research
Sentiment Analysis Tool
Analyze reviews, comments, survey text, support notes, and social signals for sentiment, themes, and evidence gaps.
Open Sentiment Analysis ToolSocial dynamics
LLM Social Simulation
Use language-model actors to inspect how group reaction, memory, and narratives may evolve.
Open LLM Social SimulationAgent rounds
Multi-Agent Simulation AI
Simulate how multiple actors respond, influence each other, and create second-order scenario paths.
Open Multi-Agent Simulation AIThe story will move
Decide before the narrative decides for you.
Bring the brief, policy, article, or statement you are already reviewing. MiroFish will turn it into a public reaction scenario you can inspect.
Start a public opinion simulation