DeepSeek sentiment tracking
Sentiment is classified on the original Chinese text with a Chinese-language classifier, not by translating first, because translation flattens exactly the hedging that carries the signal.
How it renders
Derived from the source-language answer text with the evidence 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 DeepSeek for the sentiment field, sampled n times and returned as one object per prompt.
{
"engine": "deepseek",
"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 →DeepSeek sentiment FAQ
- Which language is the classifier trained on?
- Chinese, for Chinese answers. Labels are returned with the source sentence so you can audit them.
- Can a Chinese-reading analyst check the labels?
- Yes, and we expect them to. Every label ships with its evidence.
Get Chinese sentiment classified in Chinese
Send a prompt set and we will return labels with source-language evidence.
Other DeepSeek data
Across every engine
Compare how sentiment behaves on every engine we track.
Sentiment across all engines →