Word Frequency Counter
See which words appear most often in a passage. Your work stays on this device whenever possible.
How to use Word Frequency Counter
- Paste the text into "Paste text to analyze".
- Pick "Analysis mode": Single words (Unigrams), 2-word phrases (Bigrams) or 3-word phrases (Trigrams).
- Adjust "Min word length" (default 2) and "Min occurrences" (default 1) to cut noise.
- Choose "Sort by" and "Results limit", tick or untick "Filter common stop words" and "Case-sensitive", and list extras in "Custom stop words to exclude (comma-separated)".
- Press "Analyze frequency", read the summary line, then save with "Export CSV" or "Export TXT".
Worked example
Text: "Tea or coffee? Coffee wins. Coffee, always coffee." With defaults in single-word mode the summary shows Total words 8, Filtered tokens 7 ("or" is a stop word), Unique items 4 and Lexical diversity 50.0%. The table lists coffee 4 (57.14%), then always, tea and wins with 1 each (14.29%).
When to use this tool
- Finding overused words in a first draft before editing.
- Pulling the most common two-word phrases out of a batch of customer reviews.
- Checking which three-word phrases dominate a landing page.
Important limitations
Normalizes punctuation and case sensitivity according to your settings. Phrase n-grams are evaluated within sentence boundaries. Large documents are analyzed entirely client-side without upload.
Frequently asked questions
How do stop words affect phrases?
A bigram is dropped only when both words are stop words, and a trigram only when all three are, so "the cat" survives while "of the" does not. The minimum word length applies to every word in a phrase.
What is the lexical diversity figure?
It is unique items divided by the total word count, shown as a percentage. In phrase modes the numerator counts unique phrases, so it is not a textbook type-token ratio and should be compared only within one mode.
How is text split into words?
Runs of letters and digits form words, and internal apostrophes or hyphens keep a token whole, so "mother-in-law" is one word. Case is folded unless Case-sensitive is ticked.
What base is the density percentage calculated on?
Each count is divided by the number of items that survived the filters, not by the raw word total, so removing stop words raises the percentages of the words that remain.
Is the built-in stop word list neutral?
It is English-only and contains ordinary content words such as time, work, people, year and good. Untick the filter if those words matter to your analysis.