Related tools
Why use a word frequency counter?
Spot overused terms, sketch keyword balance, compare drafts, or prep a quick term list—without uploading your manuscript.
Benefits
- Ranked list: highest counts first.
- Filters: stop words, length, occurrence floor.
- CSV: take the table to a spreadsheet.
- Live: updates as you edit.
- Private: client-side only.
How it works
A simple pipeline: normalize case, strip punctuation to spaces, split on whitespace, aggregate counts, sort, then apply your display filters.
Features
- Token rules: JavaScript \w-style normalization before split.
- Stop words: optional English small set.
- Sliders: min length 1–10; min occurrences 1–10.
- Export: two-column CSV.
- UI: scrollable responsive grid.
When to use
Editing passes, lightweight SEO checks, corpora class demos, or vocabulary surveys on pasted text.
Ideal use cases
- Writing: catch repeated fillers.
- Keywords: rough term prominence (not a rank tracker).
- Teaching: show naive tokenization.
- Logs: informal term tallies.
- QA: before specialized NLP tools.
Facts
Interpretation notes.
Key points
- Stop-word removal is English-only and limited to the built-in list.
- Stemming and lemmatization are not applied—run, runs, running count separately.
- Non-Latin scripts may not match \w tokenization as you expect.
- Minimum length uses character count of the token string after normalization.
- Very large inputs may hit browser memory limits.
Best practices
Use responsibly.
Quality considerations
- For production SEO, pair with dedicated tools and locale-aware processing.
- Preview CSV in your spreadsheet before sharing.
- Try different min-length settings to reduce noise from short tokens.
- Keep a copy of raw text before aggressive filtering.
- For code, expect keywords and strings to dominate frequencies.
When not to use
- When you need multilingual stop lists or morphological normalization.
- When legal or compliance requires audited NLP pipelines.
- When token boundaries must match a specific publisher spec exactly.
Limitations and compatibility
Naive tokenizer; English stop list; CSV export only. Requires JavaScript.
Word frequency analysis runs fully in your browser with no server upload; counts and ranked results update instantly as filters change.
Frequently asked questions
Is the word frequency counter free?
Yes. Analysis runs in your browser. No registration or upload.
What are stop words?
Very common English words (e.g. the, and, of) that you can optionally hide so the list emphasizes content words. The list is fixed and English-oriented.
How are words detected?
Text is lowercased; punctuation is turned into spaces; then tokens are split on whitespace. Only tokens matching your minimum length are counted (and stop words may be removed).
What does minimum occurrences do?
After frequencies are computed, only tokens whose count is at least that number appear in the grid and export.
Can I export the results?
Yes. Export CSV downloads the filtered table (word and count columns).
Is my text secure?
Yes. Processing stays on your device.
How is this different from a word counter?
A word counter shows totals. Here you see each distinct token and how many times it appears.