# Export TikTok Comments for Sentiment Analysis

**Use case:** 

Extract TikTok comments and reply threads for sentiment analysis and social listening. Built for data scientists and NLP researchers, it returns structured data with text, createdAt, likeCount, language, replyToCommentId, and source video details. Change profiles or postUrls to analyze any brand or viral video topic.

## Input

```json
{
  "postUrls": [
    "https://www.tiktok.com/@khaby.lame/video/7574844184952081686"
  ],
  "profiles": [
    "duolingo"
  ],
  "maxVideosPerProfile": 3,
  "maxCommentsPerPost": 50,
  "includeReplies": true,
  "maxRepliesPerComment": 5,
  "maxItems": 0,
  "minLikes": 0,
  "includeVideoMetadata": true,
  "includeCommenterDetails": false,
  "includeCommenterStats": false,
  "maxCommenterLookups": 100,
  "deepWalk": false
}
```

## Output

```json
{
  "rowType": {
    "label": "Type",
    "format": "text"
  },
  "commentId": {
    "label": "Comment ID",
    "format": "text"
  },
  "text": {
    "label": "Comment Text",
    "format": "text"
  },
  "likeCount": {
    "label": "Likes",
    "format": "number"
  },
  "createdAt": {
    "label": "Created At",
    "format": "text"
  },
  "video": {
    "label": "Video",
    "format": "text"
  },
  "postUrl": {
    "label": "Video URL",
    "format": "text"
  }
}
```

## How it works

### 1. Sign up on Apify or log in

The TikTok Comment & Reply Thread Extractor Actor is ready to run with the inputs already set for "Export TikTok Comments for Sentiment Analysis". [Sign up or log in](https://console.apify.com/create-task-from-example/xsPq5wZaUf8arjqan) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Export TikTok Comments for Sentiment Analysis" task

The TikTok Comment & Reply Thread Extractor Actor will start running based on the input automatically. You can also change all the input fields, like video urls, profiles (comments on their newest videos), and more, to match your specific use case.

### 3. Receive the "Export TikTok Comments for Sentiment Analysis" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as type, comment id, comment text, and more.

### 4. Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also [run the "Export TikTok Comments for Sentiment Analysis" task via API](https://apify.com/vexaloom-labs/tiktok-comment-and-reply-thread-extractor.md).

## About this Actor

This example demonstrates how to use [TikTok Comment & Reply Thread Extractor](https://apify.com/vexaloom-labs/tiktok-comment-and-reply-thread-extractor.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/vexaloom-labs/tiktok-comment-and-reply-thread-extractor.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

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 full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/vexaloom-labs/tiktok-comment-and-reply-thread-extractor.md

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`).