Sentiment analysis API — analyze sentiment of text and get a text sentiment scor
Sentiment analysis API — analyze sentiment of text and get a text sentiment score in one call: classifies positive / negative / neutral / mixed polarity with a -1 to +1 sentiment score, plus emotion detection in text (joy, anger, sadness, fear, surprise, disgust, trust, anticipation). Aspect-based sentiment and opinion mining for customer feedback analysis — analyze reviews, support tickets, social posts, chat messages. Via Claude Haiku.
Answeringour last check, 2026-09-24
1 of 1checks answered this week
925 msmedian answer time
$0.002listed price per call
$0.002price it asked us
Paid test badge: not yet. The checks above are free: we call the tool without paying and read the payment request it sends back. The Verified badge needs paid calls whose answers match the promised output, and nobody can buy a badge.
Endpoint
POST https://netintel.dev/sentiment/analyze
| Category | Everything else |
|---|---|
| Provider host | netintel.dev |
| Networks | eip155:8453, solana:5eykt4UsFv8P8NJdTREpY1vzqKqZKvdp |
| Payment schemes | exact |
| Self-reported calls, 30 days | 2 from 2 payers (the provider's figure, not ours) |
Our checks, last 30 days
| Day | Result | HTTP | Asked | Time |
|---|---|---|---|---|
| 2026-09-24 | valid payment request | 402 | $0.002 | 925 ms |
Example input (from the provider)
{
"body": {
"aspects": [
"food",
"service",
"price"
],
"text": "The food was absolutely delicious and the staff were so friendly, but the prices were a bit steep."
},
"bodyType": "json",
"method": "POST",
"type": "http"
}
Promised output schema (from the provider)
{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"properties": {
"input": {
"additionalProperties": false,
"properties": {
"body": {
"properties": {
"aspects": {
"description": "Optional list of up to 10 aspects for aspect-based sentiment (e.g. [\"price\", \"service\", \"quality\"]). When provided, sentiment toward each named aspect is also returned.",
"items": {
"type": "string"
},
"type": "array"
},
"text": {
"description": "The text to analyze sentiment for \u2014 a review, message, feedback, or any natural-language text. Max 10000 words or 50KB.",
"type": "string"
}
},
"required": [
"text"
],
"type": "object"
},
"bodyType": {
"enum": [
"json",
"form-data",
"text"
],
"type": "string"
},
"method": {
"enum": [
"POST"
],
"type": "string"
},
"type": {
"const": "http",
"type": "string"
}
},
"required": [
"type",
"method",
"bodyType",
"body"
],
"type": "object"
},
"output": {
"properties": {
"example": {
"properties": {
"aspects": {
"description": "Per-aspect sentiment (present only when the aspects param was supplied); each aspect maps to { polarity, score }",
"type": "object"
},
"confidence": {
"description": "Model confidence 0.0-1.0",
"type": "number"
},
"emotions": {
"description": "Detected emotions drawn from joy, anger, sadness, fear, surprise, disgust, trust, anticipation",
"items": {
"type": "string"
},
"type": "array"
},
"findings": {
"description": "Reserved \u2014 currently always [] on success (analysis errors surface as 502s, never findings)",
"type": "array"
},
"grade": {
"description": "Letter grade A-F derived from service_score",
"type": "string"
},
"polarity": {
"description": "Overall sentiment: positive, negative, neutral, or mixed",
"type": "string"
},
"score": {
"description": "Sentiment polarity score from -1.0 (very negative) to 1.0 (very positive)",
"type": "number"
},
"service_score": {
"description": "Endpoint health score 0-100 (100 on success) \u2014 distinct from the sentiment score",
"type": "number"
}
},
"type": "object"
},
"type": {
"type": "string"
}
},
"required": [
"type"
],
"type": "object"
}
},
"required": [
"input"
],
"type": "object"
}