# Social Scraper Dataset Unifier (`theendfear/factory-social-scraper-dataset-unifier`) Actor

Normalize explicit datasets from existing social media scraper Actors into one deduped cross-platform output.

- **URL**: https://apify.com/theendfear/factory-social-scraper-dataset-unifier.md
- **Developed by:** [Marco S.](https://apify.com/theendfear) (community)
- **Categories:** Marketing, Business
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$20.00 / 1,000 unified social records

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 Scraper Dataset Unifier

Normalize explicit datasets from existing social media scraper Actors into one deduped cross-platform output. This Actor does not scrape social platforms directly and does not run upstream scrapers by itself.

### What It Does

It takes records or dataset outputs from existing Instagram, TikTok, X/Twitter, Facebook, YouTube, LinkedIn, Reddit, or similar social scraper Actors and emits one normalized schema for downstream analytics, automation workflows, dashboards, and exports.

### Who It Is For

Marketing analysts, social listening teams, agencies, growth operators, and automation pipelines that already use strong platform-specific scrapers and need one predictable output format instead of separate schemas per platform.

### Input

Provide `sources`, each with `platform`, optional `actorId`, optional `datasetId`, and either direct `records` or a dataset reference. You can also provide top-level `records` for a single mixed batch.

### Output

Each row includes platform, source Actor attribution, source dataset ID, post URL or ID, author fields, normalized text, posted time, engagement counts, engagement score, engagement tier, field coverage score, record quality, missing core fields, hashtags, mentions, media URLs, canonical schema version, and a stable normalized key.

### How It Works

The Actor maps common field names used by major social scraper Actors into one schema. It validates that each record has at least an identity or content signal, normalizes counts such as `1.2k`, extracts hashtags and mentions, deduplicates by platform plus URL or post ID, computes an explicit engagement score, measures field coverage, classifies record quality, preserves source attribution, and emits only valid normalized rows.

The engagement score is deterministic: likes plus comments times two plus shares times three plus the base-10 log of views. It is a sorting and triage signal, not a claim about true reach or audience quality.

Record quality is deterministic too: a row is `strong`, `usable`, or `thin` based on whether core fields are present: identity, text, author handle, posted time, and at least one engagement signal. This is the main advantage over using separate scrapers directly: the output is not only normalized, it tells you whether the normalized row is complete enough for reporting or automation.

### Example

```json
{
  "sources": [
    {
      "platform": "instagram",
      "actorId": "apify/instagram-scraper",
      "datasetId": "abc123"
    },
    {
      "platform": "tiktok",
      "actorId": "clockworks/tiktok-scraper",
      "records": [
        { "url": "https://www.tiktok.com/@maker/video/1", "text": "Launch", "diggCount": "1.2k" }
      ]
    }
  ],
  "maxRecords": 10000
}
```

### Pricing

Recommended PAY\_PER\_EVENT event `unified_social_record_emitted`: `$0.02` per valid normalized social record. Upstream scraper costs are separate. Invalid records, duplicates, empty datasets, and charge-limited rows are not billable.

### Limitations

This is not a replacement for Instagram, TikTok, X/Twitter, or Facebook scrapers. It does not run the upstream Actor by itself, does not autonomously discover social pages, and does not bypass login, CAPTCHA, platform limits, or upstream scraper terms. It is a normalization and workflow layer over datasets the user already has permission to process.

### Integration

Use it after platform-specific scraping runs, in scheduled workflows, or as a cross-platform normalization stage before summarization, lead scoring, content intelligence, or reporting.

# Changelog

This Actor's version history is a separate document: https://apify.com/theendfear/factory-social-scraper-dataset-unifier/changelog.md

# Actor input Schema

## `sources` (type: `array`):

Array of source objects. Each source can include platform, actorId, datasetId, defaultDatasetId, and/or direct records.

## `records` (type: `array`):

Optional direct mixed social records when a single source wrapper is enough.

## `defaultPlatform` (type: `string`):

Fallback platform when direct records do not include one.

## `maxRecords` (type: `integer`):

Maximum total input records to process in one run.

## Actor input object example

```json
{
  "defaultPlatform": "unknown",
  "maxRecords": 10000
}
```

# Actor output Schema

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

Unified social records 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("theendfear/factory-social-scraper-dataset-unifier").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("theendfear/factory-social-scraper-dataset-unifier").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 theendfear/factory-social-scraper-dataset-unifier --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,theendfear/factory-social-scraper-dataset-unifier"
        }
    }
}
```

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/zl6ZaG0NUF1CD4Tyc/builds/4l6NqHeP07aBueXpn/openapi.json