Not exactly — and the tool says so. True TF-IDF needs a background corpus for the IDF part; with a single document there is no corpus, so this tool ranks by in-document frequency with a phrase bonus. It is labeled frequency-based, not TF-IDF.

Do the scores show search demand?

No. Scores measure how prominent a word is inside your text, not how many people search for it. For search demand you need a keyword research tool with real volume data.

Why are some obvious words missing?

Common English stopwords (the, and, with…) and words under 3 characters are removed by design — they add noise, not signal. Very rare words also rank low because the method is frequency-based.

How are the hashtags formed?

Each keyword is joined into CamelCase with a # prefix — "email marketing" becomes #EmailMarketing. Non-alphanumeric characters are stripped.

What is a keyword extractor?

A keyword extractor is a free online tool that gives you quick, accurate results without spreadsheets or manual math. This version runs entirely in your browser for instant, private results.

Is this keyword & tag extractor tool really free?

Yes, completely free with no account required. Use it as many times as you want — there are no usage limits or hidden paywalls.

How do I use this keyword & tag extractor tool?

Enter your details in the fields above and get instant results. Everything runs in your browser — no signup, no waiting, no data uploaded.

Keyword & Tag Extractor

What is Keyword extractor?

Keyword & Tag Extractor — Extract keywords from text free — get keywords and key phrases ranked by in-document frequency, free. Extract yours now!

Pure frequency algorithm, run entirely in your browser. Text is lowercased and tokenized; a fixed 150-word English stopword list and tokens under 3 characters are removed; remaining words are scored by occurrence count. Adjacent word pairs (bigrams) appearing at least twice get a fixed 1.5x phrase bonus; ties break alphabetically for determinism. Hashtags are CamelCase joins of the keywords. Because there is no background corpus there is no true IDF — the method is labeled frequency-based, and scores measure in-document prominence, not search volume or SEO value.

Why use this keyword extractor?

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Built for keyword extractor

Extract keywords from text free — get keywords and key phrases ranked by in-document frequency, free. Extract yours now!

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Transparent & honest

Frequency-based ranking on your text alone — scores are in-document prominence, not search demand or SEO value.

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Private by design

Everything runs in your browser. Your inputs never leave your device.

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Works everywhere

Fully responsive — perfect on desktop, tablet, and mobile. No app needed.

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Regularly updated

Regularly maintained and reviewed to ensure accuracy.

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Free forever

No accounts, no limits, no watermarks. Use Keyword & Tag Extractor as much as you need.

How to use Keyword & Tag Extractor

1Paste the text you want to analyze — an article, caption or description.
2Choose how many keywords to extract (5–50, default 15).
3Click Extract to see ranked keywords, key phrases and hashtag variants.
4Copy the hashtags for social posts, or use the keyword list to check topical focus.
5Remember: scores measure in-text prominence, not search demand.

What can you do with Keyword & Tag Extractor?

Tag generator from text — Extract keywords from text free — get keywords and key phrases ranked by in-document frequency, free.
Extract keywords online — Extract keywords from text free — get keywords and key phrases ranked by in-document frequency, free.
Seo tag extractor — Extract keywords from text free — get keywords and key phrases ranked by in-document frequency, free.

Good to know

Frequency-based ranking on your text alone — scores are in-document prominence, not search demand or SEO value.
Fixed English stopword list; other languages will extract poorly.
Bigrams need at least 2 occurrences to qualify for the 1.5x phrase bonus.

How it works

Pure frequency algorithm, run entirely in your browser. Text is lowercased and tokenized; a fixed 150-word English stopword list and tokens under 3 characters are removed; remaining words are scored by occurrence count. Adjacent word pairs (bigrams) appearing at least twice get a fixed 1.5x phrase bonus; ties break alphabetically for determinism. Hashtags are CamelCase joins of the keywords. Because there is no background corpus there is no true IDF — the method is labeled frequency-based, and scores measure in-document prominence, not search volume or SEO value.

Examples

Blog paragraph

Ranks "email marketing" (phrase, 1.5x bonus) above "email", and produces #EmailMarketing.

Caption tags

Surfaces "coffee" as the top keyword with #Coffee-style hashtag variants for the caption.

People also search for these — this tool handles them all:

keyword extractortag generator from textextract keywords onlineseo tag extractor

Frequently asked questions

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