Extract

Pull every hashtag out of social media text

Extract all hashtags from social media posts, captions, or any text block.

🛡️ Your rows never leave your browser.
Why Onfyt: Frequency counting included — see which hashtags appear most often across a batch of posts without needing a spreadsheet formula.

Interactive Sample Data

idpost_text
1Excited about this! #DataFix #OpenData #Nairobi
2Building tools for Africa #DataFix #Tech
3No hashtags in this post at all.

How this tool works

Social media managers, content analysts, and brand monitoring teams routinely need to catalogue which hashtags appear across hundreds of posts. Copying hashtags by hand from a bulk export is impractical once the dataset runs to thousands of rows. This tool scans any block of text for tokens starting with the # character followed by one or more word characters (letters, digits, underscores). It is case-insensitive by default — #DataFix and #datafix are treated as the same tag. Controls on this page: - Paste your text (raw tweets, Instagram captions, exported CSV column values) into the input panel. - Type 'extract hashtags' and click Run. - The output shows one hashtag per line. - Add 'with frequency count' to your instruction to see how many times each tag appeared. - Add 'sorted by frequency' to rank the most-used tags first. - Add 'case-sensitive' to treat #DataFix and #datafix as different tags. All extraction runs inside your browser — paste entire campaign reports without sending data to any server.

Things that usually go wrong

  • HTML-encoded hash symbols (#) inside an HTML export will not be matched — paste plain text rather than HTML source.
  • Emoji combined with hashtags (#🎉) will match the emoji as part of the tag on some platforms but not others — the extractor captures only ASCII word characters.
  • Very long hashtags may include internal underscores (#this_is_one_tag) — the whole sequence is extracted as a single tag.

Edge cases we tested

🧪 Mixed-case duplicates (#DataFix and #datafix in same text)

Treated as one tag (case-insensitive by default); count reflects combined total.

🧪 Hashtag immediately followed by punctuation (#Nairobi.)

Punctuation stripped; #Nairobi extracted correctly.

🧪 Number-only hashtag (#2024)

Matched and extracted — digits are valid hashtag characters on most platforms.

🧪 Hashtag inside a URL (https://example.com/path#anchor)

URL fragments are excluded — the # must follow whitespace or start of string to count as a hashtag.

🧪 Text with no hashtags

Returns 'No hashtags found.' rather than an error.

Frequently Asked Questions

Can I analyse hashtags from a CSV column of post texts?

Yes — paste all the cell values into the input panel separated by line breaks. The extractor scans the entire block.

Does this work for Instagram, Twitter/X, and LinkedIn hashtag styles?

Yes. All three platforms use the same # + word-character syntax.

Can I get the output as a two-column table (hashtag, count)?

Add 'as CSV with columns hashtag and count' to your instruction — the output changes to a two-column CSV ready to open in a spreadsheet.

What about mentions (@username) — can this extract those too?

Not directly, but the prompt accepts 'extract mentions' as a variant — the pattern switches from # to @.

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