Keyword Extractor
Extract the most significant keywords from text by removing a built-in list of common English stopwords and ranking what remains by frequency.
How to extract keywords from text
Paste any text into the box above. This tool splits it into words, filters out a built-in list of common English stopwords (like "the", "is", and "and"), counts what remains, and shows the top 20 most frequent meaningful words as keywords — updating live as you type.
How keyword extraction works here
This is a frequency-based extraction approach: after removing stopwords, the words that appear most often are treated as the text's keywords. It's a simple, transparent method that works well as a starting point for tagging, SEO metadata, or a quick summary of a document's subject matter — though it doesn't understand meaning or context the way more advanced NLP techniques do.
Example
Pasting a product description that repeats "wireless", "headphones", and "battery" surfaces those words as top keywords, while words like "the", "with", and "and" are filtered out automatically.
Common Use Cases
- Generating candidate tags or meta keywords for a blog post or product page.
- Quickly identifying the main topics of a long document.
- Building a starting keyword list for SEO research.
FAQs
What stopwords are filtered out?
A built-in list of over 100 common English words — articles, pronouns, prepositions, conjunctions, and auxiliary verbs like "the", "is", "and", "you", and "would" — is excluded before ranking the remaining words by frequency.
How is this different from the Keyword Density Analyzer?
The Keyword Density Analyzer reports each word's percentage share of the total text, aimed at SEO over-optimization checks. This tool focuses purely on ranking the most frequent non-stopword terms as a simple keyword list, which is more suited to tagging or quick topic identification.
Does it understand synonyms or context?
No — this is a straightforward frequency-count approach after stopword removal. It doesn't merge synonyms, understand grammar, or weigh a word's importance by anything other than how often it appears.