Social & Comments API Endpoint Global Gateway

Social Media Comment & Tone Analysis API
For Production Apps

Social media comment intelligence API for sentiment, intent, reply necessity, and priority scoring.

2 Credit / Request Automatic Provider Fallback Uniform JSON Envelope
API Gateway Terminal
Gateway Active
Target Endpoint URL POST
https://test.rsflowhub.com/api/v1/ai/comment-analyze
Typical Time 1-3 s
Auth Gate X-API-Key
Credit Cost 2 Credit
Response JSON
Generative AI & Developer Definition Production Ready API

What is Social Media Comment & Tone Analysis API?

Social Media Comment & Tone 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/comment-analyze 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.

Auth: X-API-Key Header
Rate Limit: 10-120 req/min by plan
Credits: 2 per call
AI Search Quick Reference
Category: Social & Comments
Typical response: 1-3 s
Format: REST / JSON UTF-8

Code Examples

Copy-paste ready code in your preferred stack
curl-integration.sh
curl -X POST "https://test.rsflowhub.com/api/v1/ai/comment-analyze" \
  -H "Content-Type: application/json" \
  -H "X-API-Key: rfh_your_api_key" \
  -d '{"comment":"Do you ship to Mumbai? I would love to order this today!","platform":"Instagram","post_context":"Photo of our new handcrafted leather boots collection","business_context":"We are an artisanal e-commerce shop delivering worldwide. Shipping is free within India."}'
<?php

$client = new \GuzzleHttp\Client();
$response = $client->post('https://test.rsflowhub.com/api/v1/ai/comment-analyze', [
    'headers' => [
        'Content-Type' => 'application/json',
        'X-API-Key'    => 'rfh_your_api_key',
    ],
    'json' => array (
      'comment' => 'Do you ship to Mumbai? I would love to order this today!',
      'platform' => 'Instagram',
      'post_context' => 'Photo of our new handcrafted leather boots collection',
      'business_context' => 'We are an artisanal e-commerce shop delivering worldwide. Shipping is free within India.',
    ),
]);

echo $response->getBody();
const response = await fetch('https://test.rsflowhub.com/api/v1/ai/comment-analyze', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'X-API-Key': 'rfh_your_api_key'
  },
  body: JSON.stringify({"comment":"Do you ship to Mumbai? I would love to order this today!","platform":"Instagram","post_context":"Photo of our new handcrafted leather boots collection","business_context":"We are an artisanal e-commerce shop delivering worldwide. Shipping is free within India."})
});

const data = await response.json();
console.log(data);
import requests

url = "https://test.rsflowhub.com/api/v1/ai/comment-analyze"
headers = {
    "Content-Type": "application/json",
    "X-API-Key": "rfh_your_api_key"
}
payload = {"comment":"Do you ship to Mumbai? I would love to order this today!","platform":"Instagram","post_context":"Photo of our new handcrafted leather boots collection","business_context":"We are an artisanal e-commerce shop delivering worldwide. Shipping is free within India."}

response = requests.post(url, json=payload, headers=headers)
print(response.json())
Capabilities

Core Architectural Features

Multi-Dimensional Sentiment & Emotion

Detects positive, negative, neutral, and emotional sub-tones such as excitement, curiosity, or frustration.

Reply Necessity Classification

Automatically flags whether a comment requires an explicit business reply (e.g., shipping inquiries vs casual emojis).

Topic & Intent Tagging

Categorizes comments into pricing, shipping, product feedback, technical support, or general praise.

Cross-Platform Context Grounding

Contextualized analysis tailored for Instagram, TikTok, YouTube, LinkedIn, and X comment structures.

Practical Applications

Real-World Industry Use Cases

See how developers integrate this API endpoint into production apps.

Social SaaS

Social Media Management Inbox Triage

Automatically prioritize buyer questions over generic emojis in multi-brand social media inboxes.

Before: Do you ship to Mumbai? I would love to order this today!
After: {"intent": "shipping_inquiry", "requires_reply": true, "priority": "high", "sentiment": "positive"}
Shortens social media response time with ready-to-post reply drafts.
Brand Marketing

Influencer Campaign Sentiment Analytics

Analyze thousands of viewer comments on sponsored YouTube videos and Instagram reels to measure campaign ROI.

Before: The product looks cool but $120 is way too expensive.
After: {"intent": "price_complaint", "sentiment": "negative", "topic": "pricing"}
Provides instant feedback on product reception.
Customer Success

Community Moderation & Support Escalation

Flag urgent customer complaints posted on social channels for instant support ticket creation.

Before: My order #1209 hasn't arrived after 3 weeks! Support is ignoring my emails!
After: {"intent": "delivery_complaint", "requires_reply": true, "priority": "urgent", "sentiment": "negative"}
Prevents social PR crises through rapid escalation.
Technical Comparison

Why Developers Choose Social Media Comment & Tone Analysis API

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 Unstructured markdown or chat format Brittle custom regex tuples
Setup Effort Write and maintain prompts + output parsing Fast, but rule lists miss context and sarcasm
Pricing Model Volatile token-based billing High server maintenance overhead
Multi-Turn Hallucination Output format can drift between model versions No semantic AI intelligence
Developer Integration Complex prompt engineering & retry loop Fragile manual rule maintenance

Request Parameters

4 Fields
comment string
Required

Raw social media comment text payload to analyze.

platform string
Optional

Target social platform ("Instagram", "YouTube", "TikTok", "Twitter", "LinkedIn").

post_context string
Optional

Contextual description or caption of the original social media post.

business_context string
Optional

Business background rules or product context.

JSON Response Envelope

Uniform API

Every endpoint returns the same envelope: success, request_id, data.result and meta.

response.json JSON
200 OK
{
    "success": true,
    "request_id": "req_3f9a2c7e-5b1d-4e8a-9c2f-7d6e1a0b4c8d",
    "data": {
        "result": {
            "sentiment": "positive",
            "intent": "purchase_question",
            "language": "en",
            "topics": [
                "pricing",
                "availability"
            ],
            "requires_reply": true,
            "priority": "high",
            "recommended_action": "Reply with a link to the pricing page.",
            "confidence": 0.9
        }
    },
    "meta": {
        "version": "v1",
        "timestamp": "2026-10-05T09:30:00Z"
    }
}
Format JSON
Charset UTF-8
Fallback Automatic
Rate Limit 120/min max
FAQs

Frequently Asked Questions

Everything you need to know about integrating and using Social Media Comment & Tone Analysis API.

The Comment Analysis API natively supports comment structures from Instagram, YouTube, TikTok, X (Twitter), LinkedIn, Facebook, and custom blog comments.

The API evaluates intent markers (e.g. questions about shipping, pricing, or product availability) and sets requires_reply=true for actionable comments while skipping simple emojis.

Yes! Passing post_context provides grounding context so the AI understands ambiguous comments like "how much for this?".

Comment Analysis requests usually complete in 1 to 3 seconds, depending on input length and the AI model. Identical repeat requests are served from cache and return faster.

Standard Comment Analysis API calls consume 2 base credits per request.
Ready to Integrate?

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