TikTok comments are a goldmine of unfiltered audience feedback. They tell you what people actually think about a product, a trend, or a creator in ways that polished metrics like view counts never will. But TikTok does not give you any way to export or download comments from its app. If you want to analyze comments at scale, you need a TikTok comment exporter.
This guide covers why you would want to export TikTok comments, the data you get, and two ways to do it: a free browser tool and the programmatic API approach.
Why export TikTok comments?
Here are the most common use cases:
Sentiment analysis
Want to know how people feel about your brand, a competitor, or a product launch? Export the comments from relevant videos and run them through a sentiment analysis pipeline. You will get a clear read on positive, negative, and neutral sentiment that no dashboard metric can provide.
Content ideas
TikTok comments are full of questions, requests, and suggestions. Export comments from your top-performing videos and look for patterns. What are people asking for? What confuses them? What do they want more of? These are direct content ideas from your audience.
Competitor research
Export comments from competitor videos to understand their audience’s pain points, complaints, and praise. This gives you positioning insights you cannot get any other way.
Brand monitoring
Track how your brand is mentioned in comments across TikTok. Export comments from videos that mention your brand or product and monitor sentiment over time.
Influencer vetting
Before partnering with a creator, export comments from their recent videos. Are the comments genuine or full of bot-like responses? Do their followers actually engage with the content? Comment quality tells you more about an influencer’s audience than follower count.
Academic research
Researchers studying social media behavior, content virality, or online discourse need comment data in structured formats for analysis. Exporting to CSV or JSON makes it possible to run statistical analysis, NLP, and other research workflows.
What data do you get from exported TikTok comments?
Each exported comment includes:
| Field | Description |
|---|---|
| Comment text | The full comment content |
| Author username | The TikTok handle of the commenter |
| Author nickname | The display name of the commenter |
| Like count | Number of likes on the comment |
| Reply count | Number of replies to the comment |
| Timestamp | When the comment was posted (Unix timestamp) |
| Is pinned | Whether the video creator pinned this comment |
| Is liked by author | Whether the video creator liked this comment |
| Language | Language code of the comment |
| Replies | Nested reply comments with the same fields |
Method 1: Use the free TikTok comment exporter tool
The fastest way to export TikTok comments is with the free TikTok Comments Tool on CreatorCrawl. No sign-up required for basic usage.
- Go to creatorcrawl.com/free-tools/tiktok-comments
- Paste a TikTok video URL
- Click export
- Download the results as JSON or copy them directly
This is perfect for one-off exports when you just need comments from a single video.
Method 2: Export TikTok comments with the API
For recurring exports, bulk analysis, or integration into your own tools, use the CreatorCrawl API.
Setup
- Sign up for CreatorCrawl (250 free credits, no card required)
- Generate an API key from your dashboard
Basic comment export
Python:
import requests
API_KEY = "your_api_key_here"
BASE_URL = "https://api.creatorcrawl.com/v1"
video_url = "https://www.tiktok.com/@charlidamelio/video/7321456789012345678"
response = requests.get(
f"{BASE_URL}/tiktok/video/comments",
params={"url": video_url},
headers={"x-api-key": API_KEY}
)
data = response.json()
print(f"Total comments: {data['total']}")
for comment in data["comments"]:
print(f"@{comment['user']['unique_id']}: {comment['text']}")
print(f" Likes: {comment['digg_count']} | Replies: {comment['reply_comment_total']}")
JavaScript:
const API_KEY = 'your_api_key_here'
const BASE_URL = 'https://api.creatorcrawl.com/v1'
const videoUrl = 'https://www.tiktok.com/@charlidamelio/video/7321456789012345678'
const response = await fetch(
`${BASE_URL}/tiktok/video/comments?url=${encodeURIComponent(videoUrl)}`,
{ headers: { 'x-api-key': API_KEY } }
)
const data = await response.json()
console.log(`Total comments: ${data.total}`)
for (const comment of data.comments) {
console.log(`@${comment.user.unique_id}: ${comment.text}`)
console.log(` Likes: ${comment.digg_count} | Replies: ${comment.reply_comment_total}`)
}
Export all comments with pagination
Most videos have more comments than a single API call returns. Use the cursor to paginate through all of them:
def export_all_comments(video_url):
all_comments = []
cursor = None
while True:
params = {"url": video_url}
if cursor:
params["cursor"] = cursor
response = requests.get(
f"{BASE_URL}/tiktok/video/comments",
params=params,
headers={"x-api-key": API_KEY}
)
data = response.json()
comments = data.get("comments", [])
all_comments.extend(comments)
print(f"Fetched {len(all_comments)} of {data.get('total', '?')} comments")
if not data.get("has_more"):
break
cursor = data.get("cursor")
return all_comments
comments = export_all_comments(
"https://www.tiktok.com/@charlidamelio/video/7321456789012345678"
)
print(f"Exported {len(comments)} total comments")
Save to CSV
Export your comments to a CSV file for analysis in Excel, Google Sheets, or a data tool:
import csv
def save_comments_to_csv(comments, filename="comments.csv"):
with open(filename, "w", newline="", encoding="utf-8") as f:
writer = csv.writer(f)
writer.writerow([
"username", "nickname", "comment", "likes",
"replies", "timestamp", "pinned", "liked_by_author", "language"
])
for comment in comments:
writer.writerow([
comment["user"]["unique_id"],
comment["user"]["nickname"],
comment["text"],
comment["digg_count"],
comment["reply_comment_total"],
comment["create_time"],
comment["author_pin"],
comment["is_author_digged"],
comment["comment_language"],
])
print(f"Saved {len(comments)} comments to {filename}")
save_comments_to_csv(comments)
Tips for analyzing exported TikTok comments
Look at pinned and author-liked comments first
Pinned comments and comments liked by the video author are signals of what the creator considers important. Filter for author_pin == True and is_author_digged == True to surface these.
Sort by like count for top reactions
The most-liked comments represent the strongest audience reactions. Sort your export by digg_count descending to find the comments that resonated most.
Filter by language
If you are analyzing a specific market, filter comments by the comment_language field. This is especially useful for creators with global audiences.
Track reply threads
Comments with high reply_comment_total values indicate topics that sparked conversation. These are often the most valuable for understanding audience opinions.
Run basic sentiment at scale
Export comments from multiple videos and use a simple sentiment library (like TextBlob for Python or Sentiment for Node.js) to score each comment. Aggregate scores give you a sentiment trend over time.
from textblob import TextBlob
positive, negative, neutral = 0, 0, 0
for comment in comments:
sentiment = TextBlob(comment["text"]).sentiment.polarity
if sentiment > 0.1:
positive += 1
elif sentiment < -0.1:
negative += 1
else:
neutral += 1
total = len(comments)
print(f"Positive: {positive/total*100:.1f}%")
print(f"Negative: {negative/total*100:.1f}%")
print(f"Neutral: {neutral/total*100:.1f}%")
Next steps
Now that you can export and analyze TikTok comments:
- Try the free tool at TikTok Comments Exporter
- Read the API reference for the comments endpoint
- Explore more comment use cases in the TikTok comments guide
Get started with 250 free credits and start exporting TikTok comments today.