Counting how often each word appears is the simplest way to see what a piece of text is really about. It powers keyword research, content audits, and quick readability checks. This word frequency analyzer tokenizes your text, counts every word, and shows the results as both a scaled word cloud and a ranked table, entirely in your browser.
How it works
The analyzer lowercases your text and splits it into words using a Unicode-aware pattern, so accented letters and non-Latin scripts are handled and apostrophes inside words are preserved. It then counts each distinct word.
Two options shape the result. Stop-word removal drops high-frequency filler words such as “the”, “and”, and “of” using a built-in list for the language you select, which lets the meaningful terms rise to the top. A minimum word length filter removes very short tokens. The word cloud sizes each word by its frequency relative to the most common one, and the table lists counts and each word’s percentage share of the filtered total.
Practical uses by workflow
SEO and content auditing
Paste a page’s body copy and enable stop-word removal. The resulting table shows your keyword density at a glance. If the top five words are all variants of your target keyword you are well-focused; if they are brand names or navigation fragments that leaked into the paste, your content structure may need review. The percentage column is more useful than raw counts here because it shows share of meaningful words.
Checking a draft for overused words
Writers paste a draft and look for words that appear more than expected — “very”, “really”, “just”, “quite” cluster near the top when a piece leans on filler intensifiers. The word cloud makes this visible at a glance because the most frequent word is rendered largest.
Comparing two documents
Run the tool on each document separately and note the top-20 words in the table. Documents covering the same topic should share a recognisable set of high-frequency terms. Very different top-word lists on nominally similar documents can signal a topic drift or that two pieces are duplicating rather than complementing each other.
Multilingual analysis
The stop-word lists cover English, Spanish, French, and German. For other languages, turn off stop-word removal and raise the minimum word length to 4 or 5 characters to filter out the short particles that tend to dominate (articles, prepositions, conjunctions) without a dedicated stop list.
Understanding the output
Word cloud: words are sized by frequency relative to the most common word. The largest word appeared most often; words at the same visual size appeared about the same number of times. The cloud is not a tightly packed graphic — it is a readable, selectable layout that lets you click individual words.
Table: sorted by count descending, with count and percentage. The percentage is each word’s share of the post-filter total, not the raw document length, so it stays meaningful even after removing stop words.
Counts are case-insensitive: “The”, “THE”, and “the” are all merged into a single entry. Apostrophes inside words are preserved, so “don’t” and “dont” count separately.
Tips
If a few short function words still dominate despite stop-word removal, raise the minimum word length slider — filtering to 4+ characters removes most remaining particles. For keyword-density work, the percentage column is the signal to read, not raw counts. Everything runs locally, so private drafts and confidential documents never leave your device.