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Export TikTok Comments for Sentiment Analysis

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.

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TikTok Comment & Reply Thread Extractor
TikTok Comment & Reply Thread Extractorvexaloom-labs/tiktok-comment-and-reply-thread-extractor
Type
Comment ID
Comment Text
Likes
+3 fields
Text
Number
Boolean
List
Object

Input

Profiles (comments on their newest videos):duolingo
Max comment rows per video:50
Max videos per profile:3
Include replies:true
Include video metadata:true

Output fields

Type
Comment ID
Comment Text
Likes
Created At
Video
Video URL

How it works

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 and you'll land in Apify Console with a copy of this exact task.

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 profiles (comments on their newest videos), max comment rows per video, and more, to match your specific use case.

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.

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.

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Integrate "Export TikTok Comments for Sentiment Analysis" into your workflow

Connect "Export TikTok Comments for Sentiment Analysis" with 100+ integrations, or run it via API or MCP.

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