# Social Comments Intelligence — AI on Any Social Scraper (`noniner/social-comments-intelligence`) Actor

Point it at any social comment scraper's dataset (Instagram, TikTok, YouTube, X/Twitter, Reddit) and get AI sentiment, themes, questions, complaints and an insight report.

- **URL**: https://apify.com/noniner/social-comments-intelligence.md
- **Developed by:** [Fredrik Hansson](https://apify.com/noniner) (community)
- **Categories:** AI, Social media
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$500.00 / 1,000 insights reports

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Social Comments Intelligence — AI on Any Social Scraper

Already scraping comments? Turn them into strategy. Point this at **any social comment scraper's dataset** and get an AI insight report — regardless of platform.

Works with the output of **Instagram, TikTok, YouTube, X/Twitter and Reddit comment scrapers** — it auto-detects the comment-text field.

### What you get

- **Sentiment** breakdown
- **Top themes** people keep raising
- **Top questions** your audience is asking (answer them → content)
- **Top complaints** and **standout positives**
- **Content ideas** — what to post or address next

### How to use

1. Run any social comment scraper on Apify (Instagram, TikTok, YouTube, X, Reddit…).
2. Copy its **dataset ID**.
3. Run this actor with that `datasetId`. It detects the field automatically.

```json
{ "datasetId": "YOUR_COMMENTS_DATASET_ID", "subject": "our product launch post", "maxComments": 400 }
```

### Pricing

Pay per insight report — one cost-effective AI pass over the batch.

### Note

Insights are AI-generated from the comments you provide — a strong signal, not a guarantee. It never reproduces full comments or usernames.

Actively maintained.

***

**Part of the [No Niner](https://noniner.io) toolkit** — no-code web scraping, enrichment & AI data tools, all pay-per-use. Browse the full set at **[noniner.io](https://noniner.io)**.

# Actor input Schema

## `datasetId` (type: `string`):

The dataset ID from any social comment scraper's run (Instagram, TikTok, YouTube, X/Twitter, Reddit…). The actor auto-detects the comment text field.

## `textField` (type: `string`):

Force a specific field name for the comment text (e.g. 'text', 'comment', 'content'). Leave empty to auto-detect.

## `subject` (type: `string`):

Optional label for the post/brand/campaign being analyzed, used in the report.

## `maxComments` (type: `integer`):

Cap on how many comments to read.

## `model` (type: `string`):

gpt-4o-mini is the cost-effective default.

## Actor input object example

```json
{
  "maxComments": 400,
  "model": "gpt-4o-mini"
}
```

# Actor output Schema

## `results` (type: `string`):

All rows in the default dataset.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("noniner/social-comments-intelligence").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("noniner/social-comments-intelligence").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call noniner/social-comments-intelligence --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,noniner/social-comments-intelligence"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/gd5JWl3lRdFFsgZ99/builds/5dhWzcG64gF5OTZE6/openapi.json