Word Frequency Ranker
Rank words by how often they appear in your text. Useful for SEO keyword checks, vocabulary reviews, and spotting overused terms.
Word Frequency Ranker
How word frequency ranking works
The tool splits your text into tokens, counts each word, then sorts by count (highest first). Absolute counts show raw usage. Relative frequency (percent or per-thousand words) makes it easier to compare documents of different lengths.
Filters matter more than people expect. Stop-word removal, minimum length, and occurrence thresholds cut noise so content words surface. Optional stemming or lemmatization groups variants like "run" / "running" when you want vocabulary size rather than exact spelling.
When to use it
Content and SEO
- Check keyword density without guessing
- Compare your page to a competitor draft
- Spot brand voice drift (same phrases repeated)
Research and teaching
- Corpus or author style sketches
- Reading-level vocabulary lists
- Feedback mining for common complaint words
Practical tips
Normalize case unless you care about proper nouns. Strip punctuation before counting if you are comparing plain vocabulary. Export CSV or JSON when you need the ranking in a spreadsheet or another tool.
Zipf-like skew is normal: a few words dominate, most appear once. That is not a bug. Focus on mid-frequency content words when you are optimizing for topic coverage.
Related Tools and Resources
Frequently Asked Questions
How does ranking differ from a simple word count?
Ranking sorts by frequency and can normalize by length, filter stop words, and group related forms. A plain count only tallies tokens.
What filters are available?
Typical options include stop-word lists, minimum length, minimum occurrences, and custom include/exclude lists. Use them when common words drown out the terms you care about.
How does this help SEO?
You see which terms actually dominate the page. That helps you adjust density, fill topic gaps, and avoid stuffing the same keyword.
What can I export?
Depending on the tool UI, expect CSV, JSON, or copyable tables. Charts and word clouds are separate if you need visuals.
Does it handle other languages?
Unicode text is fine for many languages. Tokenization quality varies by script; languages without clear word spaces need different rules.
Can I compare multiple documents?
Run each document separately and compare relative frequencies, or paste them into one analysis if you only need a combined ranking.
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