Use the free Extract Hashtags from Text below: your data never leaves your browser — all work happens on your device, and nothing is uploaded to any server.
Why hashtags end up scattered
Hashtags live inside captions, comments, video descriptions and notes. A creator writes them at the end of a post, a team brainstorms them in a chat, a researcher collects them from many posts about one topic. When it is time to reuse them, they are scattered across all those places, mixed in with ordinary words.
Copying them by hand is fiddly work. It is easy to drop the # from one, to miss one at the end of a line, or to copy the same tag twice. An extractor gathers them all in one pass and gives you a clean list that is ready to paste into the next post.
How this tool works
Paste any text and press Extract hashtags. The tool finds every # followed by letters, numbers or underscores, including accented letters and letters from other alphabets. Each hashtag goes on its own line in the result.
Remove duplicates, on by default, keeps each tag once, which matters because the same popular tag usually appears many times in a set of posts. Sort A to Z arranges the tags alphabetically, which helps when you are comparing sets or building a standard set for a brand. Copy the result with one button.
Common uses
Social media creators reuse a proven set of tags across posts instead of retyping them each time. They also audit their own posts: extracting the tags from a month of captions shows which tags they actually used, versus the ones they meant to use.
Marketers collect the tags around a campaign, a product launch or an event, then count and compare them. Researchers gather tags from a sample of posts to study how a topic is discussed. Community managers build a starter set for a new account from the tags that similar accounts use.
What counts as a hashtag
On most platforms a hashtag starts with # and continues with letters, digits and underscores until it hits a space or punctuation. This tool follows that rule, with one extension: it accepts Unicode letters, so tags in Spanish, French, Arabic and other languages are matched in full rather than cut off at the first accented character.
A # followed by a space is not a hashtag, and a # inside a number like “issue #5” is matched as “#5” only when the digits directly follow the symbol, which is how platforms treat it. A tag cut off by punctuation ends at the punctuation, so “#travel!” becomes “#travel”.
Using hashtags well
A clean list is only the start. Too many tags dilute a post, and irrelevant tags annoy readers and can trigger spam filters. Most platforms reward a small set of relevant tags over a long generic list. Use the extracted list to choose deliberately, not to paste everything at once.
Keep a master list for each topic or account, and update it when you discover tags that perform well. Retire tags that stopped being relevant, and check a tag before adopting it: some tags are used for unrelated or sensitive content, and appearing under them sends the wrong signal.
Privacy
Everything runs in your browser, so the text you paste is never uploaded. That matters when the text includes unpublished drafts, private group discussions or client material. Extract, copy and move on, with nothing sent to a server.
Tips
Extract from several posts at once to build a frequency picture: the tags that survive deduplication across many posts are your core set, and the ones that appear once are experiments. Sort the list when you want to compare it against a master list, and keep the original order when you want to preserve the emphasis of the original post, since authors usually put their most important tags first.