{"uid":"cap_EL7ZUhh8GvJoGX9reerU6","slug":"netintel-sentiment-analyze-c5e25406","name":"NetIntel Sentiment Analyze","description":"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.","url":"https://netintel.dev/sentiment/analyze","method":"POST","headers":{},"bodySchema":{"type":"object","$schema":"https://json-schema.org/draft/2020-12/schema","required":["input"],"properties":{"input":{"type":"object","required":["type","method","bodyType","body"],"properties":{"body":{"type":"object","required":["text"],"properties":{"text":{"type":"string","description":"The text to analyze sentiment for — a review, message, feedback, or any natural-language text. Max 10000 words or 50KB."},"aspects":{"type":"array","items":{"type":"string"},"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."}}},"type":{"type":"string","const":"http"},"method":{"enum":["POST"],"type":"string"},"bodyType":{"enum":["json","form-data","text"],"type":"string"}},"additionalProperties":false},"output":{"type":"object","required":["type"],"properties":{"type":{"type":"string"},"example":{"type":"object","properties":{"grade":{"type":"string","description":"Letter grade A-F derived from service_score"},"score":{"type":"number","description":"Sentiment polarity score from -1.0 (very negative) to 1.0 (very positive)"},"aspects":{"type":"object","description":"Per-aspect sentiment (present only when the aspects param was supplied); each aspect maps to { polarity, score }"},"emotions":{"type":"array","items":{"type":"string"},"description":"Detected emotions drawn from joy, anger, sadness, fear, surprise, disgust, trust, anticipation"},"findings":{"type":"array","description":"Reserved — currently always [] on success (analysis errors surface as 502s, never findings)"},"polarity":{"type":"string","description":"Overall sentiment: positive, negative, neutral, or mixed"},"confidence":{"type":"number","description":"Model confidence 0.0-1.0"},"service_score":{"type":"number","description":"Endpoint health score 0-100 (100 on success) — distinct from the sentiment score"}}}}}}},"responseSchema":{"type":"json","example":{"grade":"A","score":0.2,"aspects":{"food":{"score":0.9,"polarity":"positive"},"price":{"score":-0.4,"polarity":"negative"},"service":{"score":0.8,"polarity":"positive"}},"emotions":["joy","trust"],"findings":[],"polarity":"mixed","confidence":0.86,"service_score":100}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.002","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.002/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.002","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.002","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_q_sQne04xzh9kA8cFSTtO","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.002","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Analyzes text for sentiment, returning a grade, polarity score, aspect-level breakdown, emotions, and confidence level","exampleAgentPrompt":"Can you analyze the sentiment of this restaurant review and break it down by aspect — food, price, and service — with an overall grade and confidence score? The review is: 'The pasta was absolutely delicious and the staff were wonderful, but we paid way too much for the portion sizes.'","exampleUseCases":null,"resultDescription":"Returns a JSON object with an overall letter grade (e.g. 'A'), a numeric sentiment score, per-aspect scores and polarity labels (e.g. food, price, service), a list of detected emotions (e.g. joy, trust), overall polarity (positive/negative/mixed), a confidence score (0–1), and a service_score integer. Also includes a findings array for any notable observations.","failureModes":["Empty or missing text input returns a validation error","Text that is too short or ambiguous may yield low confidence scores","Non-English text may degrade aspect detection accuracy","Network timeout on very long text inputs","Payment failure (402) if USDC balance is insufficient on Base mainnet"],"whenToPreferThis":"Use this endpoint when you need fine-grained, aspect-level sentiment analysis with emotion detection and a graded output — especially for review text covering multiple dimensions like food, price, and service. Prefer this over generic sentiment APIs when you need structured aspect breakdowns and confidence scoring rather than just a simple positive/negative classification.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-13T12:53:24.907Z","isFirstParty":false}