Twitter (X) Tweet Scraper

The official X API puts tweet data behind paid tiers, rate caps, and an approval process that can take days. If all you need are the plain facts of a tweet, that is a lot of friction. This scraper skips it. Hand it a list of tweet IDs and each post comes back as one flat row: the text, who posted it, the like and reply counts, any hashtags, and links to attached media. You don't need developer keys or a login, and there's no per-call quota to worry about.

What you get

Every tweet ID you pass becomes one row with a steady shape, so the data drops straight into a sheet or database. Three groups of fields per tweet:

• Post — postId, postUrl, postText, postedAt, languageCode, sensitiveMedia, collectedAt
• Author — authorDisplayName, authorHandle, authorUserId, authorAvatarUrl, authorVerified
• Engagement and content — likeCount, repostCount, quoteCount, replyCount, hashtagList, linkedUrls, mediaLinks

If a tweet is deleted, protected, or the ID is malformed, you still get a row carrying hasError, errorDetail, and removed so nothing silently disappears from your run.

Quick start

1. Grab the tweet IDs you want — the ID is the long number at the end of a tweet URL (x.com/anyuser/status/1899111222333444555).
2. Hit Try for free and open the input form.
3. Paste your IDs into Tweet IDs, one per line.
4. Press Start, then export the results as JSON, CSV, Excel, or XML when the run finishes.

Use cases

• Brand monitoring — pull the tweets mentioning your product and read engagement at a glance
• Academic research — gather public posts for discourse, sentiment, or network studies
• Competitor tracking — collect a rival's top posts and see which ones actually landed
• Newsroom verification — capture a tweet's text, author, and timestamp before it gets edited or deleted
• Model training data — assemble labelled text and engagement signals for an NLP dataset
• Content archiving — keep a permanent copy of tweets that matter to your team

Input

Field	Type	Required	Description
tweetIdList	array of strings	Yes	Numeric tweet IDs to collect. Each ID is the number at the end of a tweet URL. Every ID is fetched independently.

Example input

{
    "tweetIdList": [
        "1899111222333444555",
        "1846200900100200300",
        "1772345678901234567",
        "1700112233445566778",
        "1623456789012345678"
    ]
}

Output

Each tweet ID produces one row. Successful rows carry the full post, author, and engagement fields; rows that fail carry the error fields instead, so your dataset stays predictable.

Example output

{
    "postId": "1899111222333444555",
    "postUrl": "https://x.com/datatrails/status/1899111222333444555",
    "postText": "Shipped a new export format today. CSV, JSON, and Excel all in one click.",
    "postedAt": "2026-02-18T09:42:11.000Z",
    "authorDisplayName": "Data Trails",
    "authorHandle": "datatrails",
    "authorUserId": "1502288841992300000",
    "authorAvatarUrl": "https://pbs.twimg.com/profile_images/1502288/avatar_normal.jpg",
    "authorVerified": true,
    "likeCount": 248,
    "repostCount": 31,
    "quoteCount": 4,
    "replyCount": 17,
    "languageCode": "en",
    "sensitiveMedia": false,
    "hashtagList": ["dataviz", "opensource"],
    "linkedUrls": ["https://t.co/9pLm2QrXyz"],
    "mediaLinks": ["https://pbs.twimg.com/media/Gx7kP2QWcAA1234.jpg"],
    "collectedAt": "2026-06-30T11:29:05.123456+00:00"
}

Output fields

Field	Type	Description
postId	string	The numeric identifier of the tweet
postUrl	string	Direct link to the tweet on x.com
postText	string	The written body of the tweet
postedAt	string	When the tweet went live
authorDisplayName	string	The public name on the author's profile
authorHandle	string	The author's @ handle on X
authorUserId	string	The numeric account ID of the author
authorAvatarUrl	string	Link to the author's profile picture
authorVerified	boolean	Whether the account carries a verified badge
likeCount	integer	How many likes the tweet has
repostCount	integer	How many times the tweet was reposted
quoteCount	integer	How many quote tweets reference this post
replyCount	integer	How many replies the tweet drew
languageCode	string	The language X detected for the tweet
sensitiveMedia	boolean	Whether the attached media is flagged sensitive
hashtagList	array	Hashtags found inside the tweet
linkedUrls	array	Outbound links shared in the tweet
mediaLinks	array	Image or video URLs attached to the tweet
collectedAt	string	When this row was captured
hasError	boolean	True when the tweet could not be collected
errorDetail	string	Explanation of why a tweet failed to load
removed	boolean	True when the tweet was deleted or is unavailable

Tips for best results

• Use the ID, not the URL. The input takes the numeric ID at the tail of a tweet link, so strip everything before the final number.
• Run a small batch first. Try five or ten IDs to confirm the fields match your pipeline before pushing a long list.
• Watch the error fields. A row with hasError set to true means the tweet was deleted, made private, or the ID was wrong — check errorDetail to see which.
• Deleted tweets still return a row. The removed flag marks posts that X has taken down, so you can filter them out cleanly.
• No keys or login needed. The scraper reads public tweet data directly, so there is nothing to authenticate and no quota to top up.

How can I use Twitter (X) tweet data?

How can I use the Twitter (X) Tweet Scraper to track how a post performed? Feed in the IDs of the tweets you care about and each row comes back with likeCount, repostCount, quoteCount, and replyCount alongside the text and author. Pull the same IDs again later and compare the counts to watch engagement build over time — a simple way to measure reach without the paid X analytics tier.

How can I export tweet text and author details for research? Paste a batch of tweet IDs and the scraper returns postText, authorHandle, authorDisplayName, postedAt, and languageCode for each one. Export the dataset as CSV or JSON and you have a clean corpus ready for sentiment analysis, discourse studies, or training an NLP model — no API approval required.

How can I archive tweets before they are deleted or edited? Collect the IDs of the posts you want to preserve and run them through the scraper. Each tweet is saved as a flat row with its full text, timestamp, author, and media links. Because the row is captured at scrape time, you keep a copy of what the tweet said even if it later gets edited or taken down.

How can I pull the media and links out of a list of tweets? Every successful row includes mediaLinks for attached images and videos and linkedUrls for any outbound links shared in the post. Run your IDs through once and you get a tidy list of every asset and reference, ready to download or cross-check.

Is it legal to scrape data?

Our actors are ethical and do not extract any private user data, such as email addresses or private contact information. They only extract what the user has chosen to share publicly. We therefore believe that our actors, when used for ethical purposes by Apify users, are safe.

However, you should be aware that your results could contain personal data. Personal data is protected by the GDPR in the European Union and by other regulations around the world. You should not scrape personal data unless you have a legitimate reason to do so. If you're unsure whether your reason is legitimate, consult your lawyers.

You can also read Apify's blog post on the legality of web scraping.

Support

Questions, feature requests, or a field you'd like added? Reach out at data.apify@proton.me and we'll get back to you.