# dt0ur.online Sentiment Analysis

> dt0ur.online Sentiment Analysis is a paid API for AI agents from dt0ur.online, paid per call via x402, $0.05/call, status down (last checked 2026-10-03).

Classifies text as POSITIVE or NEGATIVE sentiment with a confidence probability score using DistilBERT SST-2

## Facts

- Endpoint: POST https://dt0ur.online/api/inference/sentiment?utm_source=zero.xyz
- Price: $0.05/call
- Payment: x402
- Status: down
- Last checked: 2026-10-03
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/dt0ur-online-sentiment-analysis-c12bca91
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_Tijl4FYewNSbTEQJTH7W6

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability dt0ur-online-sentiment-analysis-c12bca91 -d '<json body>'
```

Example prompt: Classify the sentiment of this customer review and give me the confidence score: 'The delivery was lightning fast but the packaging was completely crushed — really disappointed.'

## When to prefer this

Choose this endpoint when you need fast, binary (POSITIVE/NEGATIVE) sentiment classification with a confidence score on English text, and you want a lightweight transformer-based inference without setting up your own ML pipeline. Ideal for high-throughput review screening, comment filtering, or tone detection where a two-class output is sufficient. For multi-class or nuanced emotion detection, a more specialized model may be preferable.

## Known failure modes

- Empty or missing text field returns a validation error
- Extremely long text passages may exceed model context limits
- Ambiguous or mixed-sentiment text may yield low confidence scores near 0.5
- Non-English text may produce unreliable classification as the model is optimized for English
- Payment failure (x402) prevents inference from running

## How this service works

Classifies text sentiment (POSITIVE/NEGATIVE) with confidence probability scores using Xenova DistilBERT SST-2 transformers.

## Output

Returns a sentiment classification label (POSITIVE or NEGATIVE) along with a confidence probability score between 0 and 1, indicating how strongly the model believes the text belongs to that class.

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/dt0ur-online-sentiment-analysis-c12bca91/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from dt0ur.online](https://www.zero.xyz/host/dt0ur.online/llms.txt)