{"uid":"cap_TeEoe--Z-gqzah2u9q_OL","slug":"sentiment-scoring-api-twitter-roberta-base-sentiment-d68df308","name":"Sentiment Scoring API (twitter-roberta-base-sentiment)","description":"Sentiment scoring for caller-provided text: positive/neutral/negative with confidence. Batch up to 16 texts per call. Model: twitter-roberta-base-sentiment. Always-on, verified onchain settlement.","url":"https://srv1553682.hstgr.cloud/nlp/api/sentiment","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"text":{"type":"string","description":"single text to score"},"texts":{"type":"array","items":{"type":"string"},"maxItems":16,"description":"batch of texts (max 16)"}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.0035","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":"$0.0035/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.0035","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.0035","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_EUaWwf4AIA8Ja0-Yd0spD","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.0035","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Scores one or up to 16 texts per call as positive, neutral, or negative with confidence values using the twitter-roberta-base-sentiment model.","exampleAgentPrompt":"Score the sentiment of these three texts and tell me if each is positive, neutral, or negative with confidence: 'Amazing product, love it!', 'It arrived on time.', 'Terrible experience, never again.'","exampleUseCases":[{"title":"Social media brand monitoring","prompt":"Analyze the sentiment of these 10 recent tweets mentioning our brand and tell me which are positive, which are negative, and how confident you are for each."},{"title":"Customer review triage","prompt":"Score the sentiment of this customer review with a confidence level — positive, neutral, or negative: 'The packaging was fine but the product stopped working after two days.'"},{"title":"Support ticket tone detection","prompt":"Check whether this support message is positive, neutral, or negative so I know how urgently to escalate it: 'I've been waiting three weeks and nobody has responded to my emails.'"}],"resultDescription":"Returns a sentiment label (positive, neutral, or negative) and a confidence score (0–1) for each submitted text. When batching, results are returned as an array aligned to the input order, supporting up to 16 texts per call.","failureModes":["Batch size exceeds 16 texts — request rejected","Empty or missing both 'text' and 'texts' fields — validation error","Text too long for the model's context window — truncation or error","Payment not settled on-chain — 402 response before processing","Model inference timeout on very long or complex inputs"],"whenToPreferThis":"Choose this endpoint when you need fast, lightweight sentiment classification (positive/neutral/negative) with confidence scores on short to medium texts — especially social media posts, reviews, or support tickets — and need batch throughput up to 16 texts per call with per-call micropayment billing rather than a subscription. The twitter-roberta-base-sentiment model is specifically optimized for informal, short-form text similar to tweets, making it a strong fit for social and conversational content over formal documents.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-15T06:38:18.291Z","isFirstParty":false}