Tiktok Comments API
Extract TikTok comments at scale for sentiment analysis, brand monitoring, and understanding what real audiences actually think.
Python | 1 | import requests |
| 2 | |
| 3 | root = "https://ensembledata.com/apis" |
| 4 | endpoint = "/tt/post/comments" |
| 5 | params = { |
| 6 | "aweme_id": "7348608161672187167", |
| 7 | "cursor": 0, |
| 8 | "token": "YOUR-TOKEN-HERE" |
| 9 | } |
| 10 | |
| 11 | res = requests.get(root+endpoint, params=params) |
| 12 | print(res.json()) |
| 13 |
Why Developer Teams Use Our API
Full Comment Threads
Retrieve nested replies alongside top-level comments to reconstruct entire conversations under a video.
Sentiment Analysis Ready
Comment text arrives clean and structured, ready to feed straight into an NLP or sentiment model.
Brand Mention Monitoring
Filter extracted comment text for keywords to catch mentions of your brand as they happen.
Bulk Comment Export
Paginate through thousands of comments on a viral post without hitting a hard results cap.
Community Feedback at Scale
Understand what real viewers think about a post instead of relying on like counts alone.
Compliant Public Data Only
Only comments visible to any TikTok viewer are collected, keeping social listening within GDPR bounds.
Scrape Tiktok Data Effortlessly
Crawl comment text, usernames, and timestamps in bulk from any TikTok video, everything you need for social listening or sentiment research.
Timestamped Threads
Pull TikTok comment timestamps to track how reactions build after a video goes live.
Like Count Per Comment
See like counts on TikTok comments to surface the opinions audiences agree with most.
Research-Ready Export
Export TikTok comment datasets in a format ready for academic or market research.
Tiktok Scraping Features
Study audience reactions and community behavior on TikTok by scraping comment data at scale with our social listening API.
- Paginate through an entire TikTok comment thread instead of a capped in-app sample.
- Reconstruct nested reply conversations under any video from the returned parent-child data.
- Feed raw comment text and timestamps directly into a sentiment analysis pipeline.
- Flag comments posted by the video's own creator to separate them from audience reaction.
- Filter extracted comment text for keywords to catch brand mentions as they happen.
Starting crawling Tiktok now!
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Contact usFrequently Asked Questions
The endpoint paginates through all publicly visible comments on a video, so you can retrieve the full comment thread rather than a limited sample.
Each comment includes the commenter's username, comment text, timestamp, like count, and reply count where available.
Yes, the raw comment text and metadata returned are commonly fed directly into sentiment analysis pipelines or NLP models.
Yes, replies to top-level comments are included, so you can reconstruct full conversation threads under a post.
No fixed cap, pagination continues as long as TikTok's public comment feed has more pages, though extremely large threads may take many sequential requests to walk through fully.
Comments are returned in the order TikTok's public feed serves them, generally most-liked first for top-level comments; there's no separate sort-by-likes parameter.
Yes, a flag on each comment indicates whether it was authored by the account that posted the video, useful for separating creator replies from audience reaction.
Either works; pass the numeric video ID or the share URL and the endpoint resolves it the same way.
Yes, many customers pull comment text at scale and filter it for brand keywords to monitor mentions and community sentiment.