Scrape Twitter (X) Comments by Tweet ID - Cookieless
Pricing
from $1.50 / 1,000 results
Scrape Twitter (X) Comments by Tweet ID - Cookieless
Extract Twitter comments from any public tweet without login or cookies. Enter a Tweet ID and get replies with engagement metrics, author profiles, hashtags, media, and conversation data in JSON or CSV. Ideal for sentiment analysis, brand monitoring, and competitive research at scale.
Pricing
from $1.50 / 1,000 results
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0.0
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Surge Street
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0
Bookmarked
10
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2
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11 days ago
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Twitter (X) Comments Scraper - No Login Required
What does this scraper do?
This actor extracts comments and replies from any public Twitter post using the Tweet ID.
Enter a Tweet ID, run the actor, and receive structured comment data including engagement metrics, author profiles, hashtags, mentions, and media metadata.
No Twitter login, no cookies, no API keys required.
Cookieless architecture ensures scalable and automation-ready data collection without authentication risks.
Why scrape Twitter comments?
Twitter replies contain direct audience feedback, sentiment signals, objections, and buying intent. This makes them valuable for:
- Sentiment analysis and brand monitoring
- Product feedback mining
- Competitive research
- Influencer engagement analysis
- Identifying high-intent prospects
- Tracking viral thread performance
- Monitoring industry discussions
Because the scraper runs without login, it fits seamlessly into automated analytics pipelines.
How much will scraping cost?
The pricing for this actor is $2.50 per 1,000 scraped results. Refer to the pricing page.
Since no authentication is required, this actor avoids API rate limits and reduces operational complexity for high-volume comment extraction.
How to use the scraper
Here is a step-by-step guide:
Step 1: Find the Tweet ID:
Open the target tweet and copy the numeric ID from the URL after /status/.
Example:
https://twitter.com/username/status/1738106896777699464
Tweet ID: 1738106896777699464
Step 2: Enter input parameters:
Paste the Tweet ID into the tweetId field.
Step 3: Start the run:
Click Start to begin extraction. The actor will retrieve publicly available comments and replies.
Step 4: Export or integrate:
Download results in JSON, CSV, or Excel format, or integrate via API into your analytics tools or CRM.
Input parameters
Input example
{"tweetId": "1738106896777699464","maxResults": 500}
| Field | Type | Description |
|---|---|---|
| tweetId | String | Tweet ID extracted from the Twitter URL |
| maxResults | Number | Maximum number of comments to extract |
What data does this scraper extract?
Formats: JSON, CSV, Excel
Each comment includes:
id- Unique comment identifiertext- Full comment textdisplay_text- Cleaned text without mentions or URLslikes- Like countretweets- Retweet countbookmarks- Bookmark countquotes- Quote countreplies- Reply countviews- Impression countcreated_at- Timestampconversation_id- Thread identifierlang- Language code
Author fields:
author.rest_id- Author IDauthor.name- Display nameauthor.screen_name- Usernameauthor.description- Bioauthor.blue_verified- Twitter Blue statusauthor.sub_count- Follower count
Entities:
entities.hashtags- Hashtagsentities.user_mentions- Mentioned usersentities.media- Attached mediamedia.photo- Image URLs
All output is structured for seamless sentiment analysis, engagement tracking, and competitive intelligence workflows.
Sample Output
{"id": "1738107442452381976","text": "@elonmusk Gratitude is a musk thank you Elon https://t.co/8u6rbvMYKp","display_text": "Gratitude is a musk thank you Elon","likes": 822,"retweets": 69,"bookmarks": 4,"quotes": 2,"replies": 152,"views": "56888","created_at": "Fri Dec 22 08:01:21 +0000 2023","lang": "en","conversation_id": "1738106896777699464","author": {"rest_id": "2800216425","name": "THE CHELSEA FORUM","screen_name": "TheChelseaForum","description": "A community where fans call home","blue_verified": true,"sub_count": 259816},"entities": {"user_mentions": [{"screen_name": "elonmusk","name": "Elon Musk"}],"media": [{"type": "photo","media_url_https": "https://pbs.twimg.com/media/example.jpg"}]}}
This output is ideal for brand monitoring, audience research, lead generation, product feedback mining, and social listening automation.
Key Features:
- π Extract Twitter comments by Tweet ID
- π Capture full engagement metrics and thread data
- β‘ Structured JSON output for analytics and automation
- π Retrieve author profiles and verification indicators
- π Export-ready formats including JSON, CSV, and Excel
- β‘ Scalable architecture for viral threads
- π Fully cookieless architecture with no login required
FAQs
Does this scraper require Twitter login?
No. It operates fully cookieless without authentication.
Can it extract replies from private accounts?
No. Only publicly accessible tweets and replies can be scraped.
Is this suitable for sentiment analysis?
Yes. The structured comment text and metadata make it ideal for NLP pipelines and engagement analysis.
Other Twitter scrapers that you may find useful: