How to use Word Frequency Counter
The Word Frequency Counter analyses a body of text and produces a ranked frequency table showing how often each word appears. It supports stop-word filtering (removing common words like "the", "and", "is"), case normalisation and minimum frequency thresholds — making it a powerful tool for keyword research, plagiarism detection, text summarisation and building word clouds.
- Paste or upload the text you want to analyse into the input area.
- Toggle "Ignore stop words" to filter out common function words that dominate most texts.
- Set the minimum frequency threshold to focus on words that appear at least N times.
- Choose whether to treat the analysis as case-sensitive (default: case-insensitive).
- The ranked frequency table updates instantly; click any column header to sort by word or count.
- Export the frequency table as CSV for use in spreadsheet tools or word-cloud generators.
Your data never leaves your device — 100% private processing.
Stop words and why they matter
Stop words are the most common words in a language — articles (a, an, the), conjunctions (and, but, or), prepositions (in, on, at) and auxiliary verbs (is, are, was). They typically account for 40–50% of all word occurrences in English prose but carry almost no semantic meaning on their own. Filtering stop words reveals the content-bearing vocabulary of a text. Different NLP tasks use different stop-word lists: search engines filter stop words from queries; text classifiers may preserve them because their presence or absence can be a style signal.
Applications: keyword research and text analysis
Word frequency analysis is a foundational technique in computational linguistics and content strategy. For SEO keyword research, comparing word frequencies across top-ranking pages reveals which terms an article must cover to be semantically relevant. For academic research, frequency tables identify the most cited concepts in a corpus. In UX, frequency analysis of customer support tickets surfaces the most common problems. The Zipf's law observation — that the most frequent word appears roughly twice as often as the second, three times as often as the third, and so on — holds surprisingly well across natural languages and text genres.
| Use case | Target keyword density | Notes |
|---|---|---|
| SEO blog post (primary keyword) | 0.5%–1.5% | Higher density risks keyword stuffing penalty |
| Product description | 1%–2% | Focus on benefit language naturally |
| Academic paper | No strict target | Use synonym variation; avoid repetition |
| PPC ad copy | 2%–4% | Match keyword to ad for Quality Score |
| Meta description | 1 instance | 160 char limit; exact match improves CTR |
| General web copy | 0.5%–1% | Write naturally; use synonyms and related terms |
Worked examples
Rank word frequency
Inputs: 'the cat sat on the mat'
Result: the ×2; cat, sat, on, mat ×1 each
With stop words removed
Inputs: same text, stop-word filter on
Result: cat, sat, mat ×1 (the, on filtered out)
Case-insensitive merge
Inputs: 'Run run RUN'
Result: run ×3
Glossary
- Stop word
- A common function word (the, and, is) filtered out before frequency analysis because it adds little semantic value.
- Zipf's law
- The empirical observation that in natural language, word frequency is inversely proportional to frequency rank.
- Corpus
- A large, structured collection of text used for linguistic analysis or training language models.
- Lemmatisation
- Reducing inflected word forms to their base (lemma) so "running", "ran" and "runs" all count as "run".
- TF-IDF
- Term Frequency–Inverse Document Frequency — a weight that balances how often a word appears in a document vs how common it is across all documents.
Related reading
Frequently Asked Questions
Why use Word Frequency Counter?
- Stop-word filter removes common function words to expose the content-bearing vocabulary of your text
- Configurable minimum-frequency threshold focuses the table on words that appear more than N times
- Case-insensitive mode merges capitalised and lowercase forms so "Run" and "run" count together
- CSV export sends the ranked frequency table directly into spreadsheets or word-cloud generators
Common use cases
- Identify the dominant keywords in a competitor article to guide your own content outline
- Detect over-repeated jargon in a legal document that should be varied for readability
- Extract the most frequent words from customer support tickets to prioritise product fixes
- Verify that a target keyword appears enough times in a draft without tipping into stuffing territory
- Build the input vocabulary for a word cloud from a speech transcript or product review corpus
Get weekly tool tips & updates
New tools, power-user tips, and productivity hacks — delivered free every Friday.
No spam, ever. Unsubscribe with one click.
Related Text Tools
Sort Text Lines
Sort lines of text alphabetically, numerically, or reverse. Case-insensitive option, remove duplicates, and trim whitespace. Free online line sorter.
Remove Line Breaks
Remove line breaks and paragraph breaks from text online. Replace breaks with spaces, keep paragraphs, and strip extra spaces. Free and private.
Invisible Character Remover
Remove invisible and zero-width Unicode characters from text. Strips zero-width spaces, BOM and bidi controls and normalizes odd spaces — cleaned in your browser.
Word Counter
Count words, characters, sentences, and paragraphs, and estimate reading time. Free, instant, and private — ideal for essays, articles, and posts.
Keyword Density Checker
Analyze keyword density and word frequency in your text for SEO. See one-, two-, and three-word phrase counts. Free and private.
Case Converter
Convert text to camelCase, PascalCase, snake_case, kebab-case, UPPERCASE, lowercase, Title Case, and Sentence case instantly.
Explore all Text Tools.