# Instagram Post Intelligence — Early Commenters & Bot Signals (`autokeren/ghostfox-instagram-intel`) Actor

See WHO COMMENTED FIRST on any Instagram post — usernames, timestamps, texts. Bot-pattern heuristics (burst timing, emoji-only ratio, repeat commenters). Zero login, zero cookies, anti-detect engine.

- **URL**: https://apify.com/autokeren/ghostfox-instagram-intel.md
- **Developed by:** [auto keren](https://apify.com/autokeren) (community)
- **Categories:** Social media
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$5.00 / 1,000 post intel 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

## 🕵️ Instagram Post Intelligence — Early Commenters & Spread Signals

Deep-dive intelligence for any Instagram post — **without login and without cookies**. Powered by the Ghostfox anti-detect browser engine.

### 🔍 What you get per post

**Engagement (exact, live numbers):**

- Exact likes & total comments (via embed enrichment)

**Early commenter sample:**

- Visible commenters with usernames, relative timestamps (`3 s`, `10 s`, `4 h`) and comment text
- Captured in display order — the sample Instagram shows to logged-out visitors

**Caption intelligence:**

- Full caption + all @mentions (credit/tag chain extraction)

**Spread & bot-pattern heuristics (honestly labeled as heuristics):**

- `median_comment_gap_sec` — comments arriving in second-level bursts suggest coordinated activity
- `emoji_only_ratio` — majority emoji-only comments suggest low-effort/paid engagement
- `repeat_commenters` — same users commenting repeatedly in a small sample
- `comments_per_like` — abnormally high ratio suggests comment-buys
- Combined `bot_signal`: `low` / `medium` / `high` with human-readable `signal_notes`

### 💰 Pricing

**$5.00 per 1,000 analyzed posts** — each result is a full intelligence dossier.

### ⚙️ Input

| Field | Description |
|---|---|
| `postUrls` | Instagram post URLs or shortcodes (required) |
| `maxComments` | Max visible comments to capture per post (default 20) |
| `scrollForComments` | Scroll to load more visible comments (default true) |
| `proxy` | Optional proxy URL — recommended for jobs with many posts |

### 📊 Sample output

```json
{
  "item_type": "post_intel",
  "shortcode": "De4ydmnAMes",
  "author_username": "cristiano",
  "posted_at": "4 h",
  "caption": "71 years of passion. Happy birthday, Al Nassr! 🟡🔵",
  "mentions": [],
  "likes": 1493180,
  "comments": 15468,
  "early_commenters": [
    {"username": "sadegh_lazemi7", "time_ago": "3 s", "text": "😍😍😍"},
    {"username": "ghazale.7.7", "time_ago": "3 s", "text": "❤️"}
  ],
  "commenter_count": 8,
  "median_comment_gap_sec": 7,
  "emoji_only_ratio": 0.65,
  "bot_signal": "medium",
  "signal_notes": ["65% emoji-only comments"]
}
```

### 🔬 How it works

1. The post page loads through the anti-detect engine (coherent fingerprint, invisible capture).
2. Visible comments (logged-out sample) are extracted positionally — usernames, relative timestamps, text.
3. Exact engagement comes from the embed endpoint (public, no login).
4. Heuristics are computed over the sample and honestly reported — a *sample*, not the full comment tree (full pagination requires login).

### ⚠️ Notes

- Comment capture is the **visible logged-out sample** — for viral posts this skews to recent comments. The heuristics account for this.
- For heavy jobs, bring a residential proxy in the `proxy` field.

# Actor input Schema

## `postUrls` (type: `array`):

Instagram post URLs or shortcodes to analyze

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

Maximum visible comments to capture per post (higher = slower)

## `scrollForComments` (type: `boolean`):

Scroll the post page to load more visible comments before sampling

## `proxy` (type: `string`):

Optional proxy (residential recommended for heavy use). http://user:pass@host:port or socks5://host:port

## `pacingMode` (type: `string`):

Request pacing between posts. Randomized jitter in each mode. Use 'cautious' for large jobs.

## Actor input object example

```json
{
  "postUrls": [],
  "maxComments": 10,
  "scrollForComments": true,
  "proxy": "",
  "pacingMode": "balanced"
}
```

# Actor output Schema

## `item_type` (type: `string`):

No description

## `shortcode` (type: `string`):

No description

## `post_url` (type: `string`):

No description

## `author_username` (type: `string`):

No description

## `verified` (type: `string`):

No description

## `caption` (type: `string`):

No description

## `posted_at` (type: `string`):

No description

## `posted_at_epoch` (type: `string`):

No description

## `likes` (type: `string`):

No description

## `comments` (type: `string`):

No description

## `mentions` (type: `string`):

No description

## `first_commenters` (type: `string`):

No description

## `early_commenters` (type: `string`):

No description

## `commenter_count` (type: `string`):

No description

## `median_comment_gap_sec` (type: `string`):

No description

## `exact_median_gap_sec` (type: `string`):

No description

## `spread_window_sec` (type: `string`):

No description

## `emoji_only_ratio` (type: `string`):

No description

## `repeat_commenters` (type: `string`):

No description

## `comments_per_like` (type: `string`):

No description

## `bot_signal` (type: `string`):

No description

## `signal_notes` (type: `string`):

No description

## `sampled_comments` (type: `string`):

No description

## `data_source` (type: `string`):

No description

## `error` (type: `string`):

No description

## `scraped_at` (type: `string`):

No description

# 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 = {
    "postUrls": []
};

// Run the Actor and wait for it to finish
const run = await client.actor("autokeren/ghostfox-instagram-intel").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 = { "postUrls": [] }

# Run the Actor and wait for it to finish
run = client.actor("autokeren/ghostfox-instagram-intel").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 '{
  "postUrls": []
}' |
apify call autokeren/ghostfox-instagram-intel --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,autokeren/ghostfox-instagram-intel"
        }
    }
}
```

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/VElmfUVPA0iSJcnup/builds/Ax0t4ixTIHf6huzIm/openapi.json