Gemini app sentiment tracking
Gemini is the most hedged of the major assistants, so sentiment here skews neutral. We return the label, a confidence score and the evidence sentence so hedging is visible rather than rounded away.
How it renders
Derived from the answer text with the supporting sentence retained.
Sampling
Classifications are reported as distributions across n, because the same engine will frame the same brand differently between samples.
Gotcha
What the API returns
A single collection call against Gemini app for the sentiment field, sampled n times and returned as one object per prompt.
{
"engine": "gemini",
"field": "sentiment",
"prompt": "best ai visibility tracking tool",
"country": "GB",
"language": "en",
"n": 30,
"sentiment": [
{
"brand": "Nostimates",
"label": "recommended",
"confidence": 0.86,
"distribution": {
"recommended": 0.6,
"neutral": 0.33,
"hedged": 0.07
}
}
]
}Response fields
| Key | Type | Notes |
|---|---|---|
| brand | string | Brand the classification applies to. |
| label | string | recommended | neutral | hedged | negative. |
| confidence | float | Classifier confidence for this sample. |
| evidence | string | The sentence the label was drawn from. |
| distribution | object | Label shares across the n samples. |
What it costs
Add-on field. Priced per collection at a small multiple of the base credit.
See credit pricing →Gemini app sentiment FAQ
- Why is Gemini sentiment mostly neutral?
- Its safety framing avoids strong product claims. That is a property of the engine, and we report it as such.
- Can I filter low-confidence labels?
- Yes, every label ships with a confidence score.
Add Gemini sentiment to your engine mix
Send a prompt set and we will return the distribution with evidence sentences attached.
Other Gemini app data
Across every engine
Compare how sentiment behaves on every engine we track.
Sentiment across all engines →