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Sentiment Analyzer & Emotion Classifier
x402
Sentiment Analyzer & Emotion Classifier is a paid API for AI agents from x402-deployer.x402-deployer.workers.dev, paid per call via x402, $0.01/call, status unknown (last checked 2026-09-15).
Analyzes text to return overall sentiment (positive/negative/neutral) with a score from -1 to +1, plus per-emotion scores (joy, anger, sadness, fear, surprise, disgust) and optional aspect-based sentiment.
Price / call$0.01
Success—
StatusUnknown
How this service works
Sentiment analysis API / sentiment analyzer / text sentiment classifier / emotion classifier / aspect-based sentiment. Scores arbitrary text with overall sentiment, score (-1 to +1), per-emotion labels (joy/anger/sadness/fear/surprise/disgust), and optional aspect-based scoring. Pure text analysis endpoint for product reviews, tickets, comments, and support logs.
Output
Returns an overall sentiment label (positive/negative/neutral), a float score from -1 to +1, and a per-emotion map with scores for joy, anger, sadness, fear, surprise, and disgust. Optionally includes aspect-level sentiment scores when aspects are specified.
Example use cases
Example prompt
“Analyze the sentiment and emotions in this customer review — give me the overall score from -1 to +1 plus per-emotion breakdown: "The product arrived on time but the packaging was disappointing and the instructions made me feel completely lost."”
Technical details
Endpoint
POSThttps://x402-deployer.x402-deployer.workers.dev/sentiment-analysisWhen to prefer
Use this endpoint when you need both a coarse sentiment polarity score AND fine-grained per-emotion classification (joy, anger, sadness, fear, surprise, disgust) in a single call, especially when aspect-based scoring is also needed. Prefer over simpler positive/negative classifiers when multi-dimensional emotional insight is required.
Side effects
- Empty or missing text field returns 400 Bad Request
- Text too long may be truncated or rejected
- Payment not included or insufficient USDC returns 402 Payment Required
- Non-English text may yield lower accuracy or unexpected emotion scores
- Ambiguous or sarcastic text may produce misleading sentiment scores
Input
{
"input": {
"body": {
"text": "I really enjoyed this movie. The plot was engaging and the acting was superb, though the ending felt a bit rushed."
},
"type": "http",
"method": "POST",
"bodyType": "json"
}
}Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
{
"model": "hermes-3-llama-3.1-405b",
"source": "morpheus",
"summary": "The user enjoyed the movie overall, praising the plot and acting, but felt the ending was rushed.",
"emotions": {
"joy": 0.7,
"fear": 0.1,
"anger": 0.1,
"disgust": 0.1,
"sadness": 0.2,
"surprise": 0.3
},
"confidence": 0.8,
"input_chars": 114,
"overall_score": 0.6,
"overall_sentiment": "positive"
}Tags
x402
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