# TikTok Engagement Bot Check - Real People Or Bots? (`reapx/tiktok-comment-authenticity`) Actor

"Every comment says fire emoji and nothing else. Is any of this real?" See who keeps turning up under a TikTok creator's posts - the same handles again and again is the one thing a single video can never show you.

- **URL**: https://apify.com/reapx/tiktok-comment-authenticity.md
- **Developed by:** [Tarek Etman](https://apify.com/reapx) (community)
- **Categories:** For creators, Marketing, Social media
- **Stats:** 1 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $7.00 / 1,000 comment thread reads

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.
Actors are written with capital "A".

## 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.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

![reapX - the record of what changed](https://reapx.dev/reapx.gif)

## Real People, Or A Bot Farm?

> *"The comments are all fire emojis. Am I about to pay for an audience that does not exist?"*

An engagement pod looks exactly like a hit. Huge comment counts, instant replies, a rate that
beats anyone in your budget. **The tell is never one video** - it is the same handles showing up
under post after post, and nothing that reads a single comment section can see it.

So we read across their posts, not down one. You get the accounts that keep reappearing **by
name**, how many of their posts each one turned up under, how much of the thread is one word and
an emoji, and where that puts them among creators of the same size.

**What comes back reads like this:**

> *"9.1% of the comments across @gymshark's last 8 posts come from the same 9 accounts, about
> what creators their size get. On this one we read 32 comments of this video's 531, and only
> 3.1% of them are a single word or an emoji."*

That first number is the one that decides whether you pay them - and the handles behind it are
on the row, so you can open them and see for yourself.

### The comparison nobody else has

Every share we return is placed against **157 TikTok creators we measured ourselves**, split by
follower size, so "9.1%" stops being a number and becomes a position:

| Creators this size | Typical share of comments from repeat accounts |
|---|---|
| 1k - 10k | 8.4% |
| 10k - 100k | 6.1% |
| 100k - 1M | 3.7% |
| 1M - 10M | 4.7% |
| 10M+ | 3.5% |

Small accounts have regulars; huge ones do not. A 3% share means one thing on a 5,000-follower
creator and something else entirely on one with 20 million, which is why the row carries the
percentile inside their own band and not a single pass-or-fail line.

### ⬇️ Input

```json
{
  "handles": ["gymshark", "khaby.lame"],
  "maxPosts": 8,
  "maxComments": 50
}
```

| Field | Type | Default | Description |
|---|---|---|---|
| `handles` | Array | `["gymshark", "khaby.lame"]` | TikTok handles to read across their recent posts. A video link works too, and checks just that one. |
| `maxPosts` | Integer | `8` | How many of each creator's recent posts to compare. More posts makes the pattern harder to argue with. |
| `maxComments` | Integer | `50` | How deep to read into each comment section. |

### ⬆️ Output

One row per video, so a run over one creator returns their whole recent set with the
cross-post numbers on every row.

| Field | Type | Description |
|---|---|---|
| `whatIFound` | String | The answer in one line, ready to paste into a client deck. |
| `awemeId` | String | TikTok's own video id. The per-row key. |
| `username` | String | The creator handle exactly as TikTok returned it. |
| `recurringCommentSharePct` | Number | Share of every comment read that came from accounts appearing under more than one of their posts. |
| `recurringCommenters` | Number | How many accounts those are. |
| `recurringCoreOnThreePlus` | Number | How many turn up under three posts or more. |
| `topRecurring` | Array | Those handles, with the number of posts each commented on. |
| `peerPercentile` / `peerBand` / `peerSampleSize` | Number / String | Where they sit among creators of the same follower size, and how many we measured. |
| `standing` | String | That placing in words. |
| `fillerCommentSharePct` | Number | Share of this video's comments that are one word or an emoji and nothing else. |
| `copiedCommentSharePct` | Number | Share repeating the same wording from more than one account. |
| `commentsReadHere` / `totalComments` | Number | How many we read here, and how many the post carries. |
| `commentsPerThousandViews` | Number | This post's comment rate against its own view count. |
| `sampleComments` | Array | Five real comments with handle, likes and timestamp. |
| `postsRead` / `commentsRead` / `distinctCommenters` | Number | What the cross-post comparison spans. |
| `recurrenceReason` | String | Why a comparison is absent, when it is. Never a guess in its place. |
| `computedStatus` | Object | Where every value on the row came from. |

#### Worked output example

A real row from run `lxCScHBtnBF6M0DDF`, trimmed only for length:

```json
{
  "whatIFound": "9.1% of the comments across @gymshark's last 8 posts come from the same 9 accounts, about what creators their size get. On this one we read 32 comments of this video's 531, and only 3.1% of them are a single word or an emoji.",
  "checkStatus": "checked",
  "awemeId": "7661334167342320918",
  "username": "gymshark",
  "videoUrl": "https://www.tiktok.com/@gymshark/video/7661334167342320918",
  "playCount": 711900,
  "followerCount": 6600000,
  "postsRead": 8,
  "commentsRead": 266,
  "distinctCommenters": 232,
  "recurringCommenters": 9,
  "recurringCoreOnThreePlus": 3,
  "recurringCommentSharePct": 9.1,
  "topRecurring": [
    { "handle": "sindelar__", "postsCommentedOn": 5 },
    { "handle": "maronfitt", "postsCommentedOn": 4 },
    { "handle": "aesthetics17001", "postsCommentedOn": 3 }
  ],
  "peerBand": "1M-10M",
  "peerSampleSize": 50,
  "peerMedianSharePct": 4.68,
  "peerPercentile": 70,
  "peerBeatenCount": 35,
  "standing": "about what creators this size get",
  "commentsReadHere": 32,
  "totalComments": 531,
  "fillerCommentSharePct": 3.1,
  "copiedCommentSharePct": 0,
  "commentsPerThousandViews": 0.75,
  "sampleComments": [
    { "author": "sariminister", "text": "Does it come with David Laid?", "likes": 1840, "postedAt": "2026-07-11T18:11:10.000Z" }
  ],
  "scrapedAt": "2026-08-06T19:34:57.923Z"
}
```

### How it works

1. **The whole recent set in one request.** A creator's last posts come back together, with the
   real view count on each, so comparing across them costs nothing extra.
2. **Every comment section read on its own.** Real text, the commenter's handle, the like count
   and the timestamp - not a summary of them.
3. **The arithmetic that needs the set.** Who appears under more than one post, how many posts
   each, and what share of everything they wrote - then placed against 157 creators we measured
   the same way, inside the same follower band.
4. **The evidence stays on the row.** The handles, five real comments, the counts and the source
   of every value, because an agency cannot use a number it cannot defend.

### ❓ FAQ

##### What actually gives a pod away?

Repetition across posts. One account under one video is a fan; the same twenty under eight
videos is an arrangement. That is why this reads a creator's set rather than a single thread.

##### Does a high number prove someone bought engagement?

No, and we do not say it does. A devoted fandom makes the same shape as a bought pod - the
difference is who the accounts are, so we hand you the handles and you look. Names like
`user0998486603` under every post read differently from a fan-edit account.

##### What if a creator has only posted a couple of times?

Then the cross-post comparison is not on the row, and `recurrenceReason` says so. We would
rather return nothing than a pattern read off two posts.

##### Can it run with no input?

Yes. Every field has a working default, so an empty call returns a real answer.

##### Can I check one specific video?

Paste its link into `handles`. You get that comment section read in full; the cross-post
numbers need a creator.

### 💬 Your feedback

Need a different depth, a bigger peer sample, or the recurring accounts pushed somewhere?
reapxdev@proton.me.

***

Unofficial - not affiliated with TikTok. reapx · reapx.dev · reapxdev@proton.me

# Actor input Schema

## `handles` (type: `array`):

A TikTok handle to read across their recent posts - that is where the pattern shows up. You can also paste a single video link to check just that one.

## `maxPosts` (type: `integer`):

One account under one post is a fan. The same accounts under eight is a pattern, so more posts makes the answer harder to argue with.

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

How many comments to read per post. A bigger sample is much harder for a pod to hide in.

## Actor input object example

```json
{
  "handles": [
    "gymshark",
    "khaby.lame"
  ],
  "maxPosts": 8,
  "maxComments": 50
}
```

# Actor output Schema

## `items` (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 = {
    "handles": [
        "gymshark",
        "khaby.lame"
    ],
    "maxPosts": 8,
    "maxComments": 50
};

// Run the Actor and wait for it to finish
const run = await client.actor("reapx/tiktok-comment-authenticity").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 = {
    "handles": [
        "gymshark",
        "khaby.lame",
    ],
    "maxPosts": 8,
    "maxComments": 50,
}

# Run the Actor and wait for it to finish
run = client.actor("reapx/tiktok-comment-authenticity").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 '{
  "handles": [
    "gymshark",
    "khaby.lame"
  ],
  "maxPosts": 8,
  "maxComments": 50
}' |
apify call reapx/tiktok-comment-authenticity --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,reapx/tiktok-comment-authenticity"
        }
    }
}

```

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/Qalb2o361YzjqaT5x/builds/kifFHl06V5IHrNtU3/openapi.json