Aspect-Based Sentiment Analysis
Analyze sentiment for specific features or subjects (e.g. "pricing", "speed", "support") within a single text block.
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Aspect-based sentiment classification and emotion intensity scoring across 50+ languages.
https://test.rsflowhub.com/api/v1/ai/sentiment-analysis
Real-Time Multilingual Sentiment Analysis API is a ready-to-use REST API on RSFlowHub for developers building web, mobile and AI agent applications. Send a JSON request to POST /api/v1/ai/sentiment-analysis with your API key; RSFlowHub runs it on a tuned AI model (with automatic fallback to a backup provider) and returns a structured JSON result, usually within 1 to 3 seconds.
Tutorial: Sentiment Analysis in Laravel: Step-by-Step Tutorial with a REST API
X-API-Key Header
curl -X POST "https://test.rsflowhub.com/api/v1/ai/sentiment-analysis" \
-H "Content-Type: application/json" \
-H "X-API-Key: rfh_your_api_key" \
-d '{"text":"The dashboard is incredibly fast, but the new billing page is very confusing.","aspects":["dashboard","billing"]}'
<?php
$client = new \GuzzleHttp\Client();
$response = $client->post('https://test.rsflowhub.com/api/v1/ai/sentiment-analysis', [
'headers' => [
'Content-Type' => 'application/json',
'X-API-Key' => 'rfh_your_api_key',
],
'json' => array (
'text' => 'The dashboard is incredibly fast, but the new billing page is very confusing.',
'aspects' =>
array (
0 => 'dashboard',
1 => 'billing',
),
),
]);
echo $response->getBody();
const response = await fetch('https://test.rsflowhub.com/api/v1/ai/sentiment-analysis', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'X-API-Key': 'rfh_your_api_key'
},
body: JSON.stringify({"text":"The dashboard is incredibly fast, but the new billing page is very confusing.","aspects":["dashboard","billing"]})
});
const data = await response.json();
console.log(data);
import requests
url = "https://test.rsflowhub.com/api/v1/ai/sentiment-analysis"
headers = {
"Content-Type": "application/json",
"X-API-Key": "rfh_your_api_key"
}
payload = {"text":"The dashboard is incredibly fast, but the new billing page is very confusing.","aspects":["dashboard","billing"]}
response = requests.post(url, json=payload, headers=headers)
print(response.json())
Analyze sentiment for specific features or subjects (e.g. "pricing", "speed", "support") within a single text block.
Returns confidence scores (-1.0 to +1.0) for positive, negative, neutral, and mixed emotional tones.
Multilingual sentiment classification across English, Spanish, French, German, Hindi, Gujarati, Japanese, and more.
Fast enough for live moderation flows and batch analytics jobs.
See how developers integrate this API endpoint into production apps.
Categorize incoming customer reviews and Net Promoter Score (NPS) comments into positive and negative themes.
Monitor public social media posts and brand mentions during new feature or product launches.
Auto-flag angry or highly negative support tickets for priority routing to senior agents.
Comparing RSFlowHub's specialized API gateway vs raw multi-turn LLM prompts vs legacy regex rules.
| Evaluation Metric | RSFlowHub API | Raw LLM Prompts | Legacy Regex / Rules |
|---|---|---|---|
| Response Structure | Validated JSON envelope | Unstructured markdown or chat format | Brittle custom regex tuples |
| Setup Effort | One POST request, no prompts | Write and maintain prompts + output parsing | Fast, but rule lists miss context and sarcasm |
| Pricing Model | Flat 1 credit/request | Volatile token-based billing | High server maintenance overhead |
| Multi-Turn Hallucination | Zero (Deterministic validators) | Output format can drift between model versions | No semantic AI intelligence |
| Developer Integration | 3 lines cURL, PHP, JS, Python | Complex prompt engineering & retry loop | Fragile manual rule maintenance |
text
string
Text payload to analyze for sentiment and emotional tone.
aspects
array
Optional array of specific target aspects/features to analyze (e.g. ["pricing", "support", "speed"]).
Every endpoint returns the same envelope: success, request_id, data.result and meta.
{
"success": true,
"request_id": "req_3f9a2c7e-5b1d-4e8a-9c2f-7d6e1a0b4c8d",
"data": {
"result": {
"sentiment": "mixed",
"confidence": 0.91,
"aspect_sentiments": [
{
"aspect": "dashboard",
"sentiment": "positive",
"confidence": 0.94
},
{
"aspect": "billing",
"sentiment": "negative",
"confidence": 0.89
}
]
}
},
"meta": {
"version": "v1",
"timestamp": "2026-10-05T09:30:00Z"
}
}
Everything you need to know about integrating and using Real-Time Multilingual Sentiment Analysis API.
Get started in minutes with free welcome credits and instant API key generation.
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