Understand the Emotion Behind Any Text

Sentiment Analysis API.

Analyze the emotional tone of any text. Our API returns sentiment classification (positive, negative, neutral) with comparative scores. Built for high-volume processing of customer reviews, social media posts, survey responses, and more.

Free tier, no card< 200ms responses99.9% uptime SLA
GET/v1/sentimentanalysislive
Response200 OK · sample
{
  "status": "ok",
  "error": null,
  "data": {
    "comparative": 0.25,
    "sentimentText": "positive",
    "sentiment": 3,
    "isPositive": true,
    "isNegative": false,
    "normalizedScore": 0.3
  }
}
Sample response · verify to run one live call, no signup
Integrates with your favorite tools
LangChainn8nZapierMakePipedreamPower AutomatePostman

Sentiment Analysis API

Analyze the emotional tone of any text. Our API returns sentiment classification (positive, negative, neutral) with comparative scores. Built for high-volume processing of customer reviews, social media posts, survey responses, and more.

  • Real-time sentiment classification with confidence scores
  • Process thousands of texts per second
  • Handles informal text, slang, and emojis
  • Comparative scoring for trend analysis
  1. 1

    Send one request

    A single authenticated GET with the location you care about — no SDK required.

    GET /v1/sentimentanalysis?query=
    x-api-key: your_key
  2. 2

    We do the aggregation

    Each request pulls from multiple upstream sources and computes the derived fields for you.

  3. 3

    Get clean JSON back

    One structured object, typically under 200 ms — ready to render.

    { comparative, sentimentText, sentiment, }

Everything in a single call.

/v1/sentimentanalysisapplication/json
comparative0.25
sentimentText"positive"
sentiment3
isPositivetrue
isNegativefalse
normalizedScore0.3

What developers build with it.

Real applications shipping on this endpoint today — each with the numbers that made it worth wiring up.

See every use case

Call it in your language.

Copy a working request, or install a typed SDK. Same endpoint, same key.

const res = await fetch("https://api.apiverve.com/v1/sentimentanalysis", { method: "POST", headers: { "x-api-key": "YOUR_API_KEY" } });
const { data } = await res.json();
console.log(data);

One subscription, the whole understand the emotion behind any text stack.

Every related API ships with your key — no separate plans, no extra keys, one bill.

See pricing
8APIs in this bundle
99.9%uptime SLA

Wire it into the tools you already run.

Ready-made recipes for Zapier, Make, and n8n — trigger on an event, and the data lands where your team works.

Google Sheets
Sentiment Score Feedback in Google Sheets
WhenNew row added in Google Sheets
ThenAnalyze text from row → write sentimentText, comparative, and normalizedScore back to the row
Slack
Negative Sentiment Alert in Slack
WhenNew customer feedback received
ThenAnalyze feedback text → if isNegative is true, post text with comparative score to Slack channel
Airtable
Auto-Score Reviews in Airtable
WhenNew record created in Airtable
ThenAnalyze text field → update record with sentimentText, comparative, and isPositive
Notion
Sentiment-Tagged Feedback in Notion
WhenNew database item created in Notion
ThenAnalyze text field → update Notion item with sentimentText, comparative, and isPositive
Salesforce
Case Sentiment Scoring in Salesforce
WhenNew case created in Salesforce
ThenAnalyze case description → update case with sentimentText, comparative, and normalizedScore
GitHub
Issue Sentiment Labeling in GitHub
WhenNew issue created in GitHub
ThenAnalyze issue body → add label based on sentimentText and post comparative score as comment
Browse all integrations

Questions about the API

What sentiment categories are returned?
The API returns three categories: positive, negative, and neutral. It also provides a numeric score from -5 (very negative) to +5 (very positive) and a comparative score normalized by text length.
Can it handle informal text and emojis?
Yes, our sentiment model is trained on social media data and handles informal language, slang, abbreviations, and common emojis.
How accurate is the sentiment analysis?
Our model achieves 85%+ accuracy on standard benchmarks. Accuracy is highest for clearly positive or negative text and may vary for sarcasm or highly context-dependent language.
What languages are supported?
Currently, the API is optimized for English text. Support for additional languages is planned for future releases.
Is there a text length limit?
The API accepts texts up to 10,000 characters. For longer documents, we recommend splitting into paragraphs and averaging the results.
Can I use this for customer review analysis?
Absolutely. Sentiment analysis is ideal for processing customer reviews, NPS feedback, support tickets, and survey responses at scale.

Start building with the Sentiment Analysis API. Free tier, no card required — your key is live in minutes.

Bonus: 300+ more APIs

The same key unlocks every other APIVerve endpoint — reach for them when you need them.

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