Word Frequency Counter
Paste text to count word frequencies: built-in Chinese segmentation and CN/EN stop-word lists, filters by length and language scope, with ranking you can copy or export as CSV.
| # | Word | Count | Share |
|---|
Paste text and click "Analyze"; results will appear here.
How word frequency analysis works
English words are split on spaces and punctuation. Chinese has no natural word boundaries, so the tool ships with a dictionary of common words and applies forward maximum matching — dictionary hits are segmented as words (e.g. 家庭服务器), and the rest fall back to single characters. It is fast and runs entirely in your browser, with no upload to any segmentation service.
Stop words are high-frequency function words like 的/了/the/a that carry little meaning and appear in every text; they are filtered out by default. Turn the option off to see the full counts. Minimum-length filters remove single characters or very short words when you want more meaningful keywords.
Common uses: SEO keyword density analysis (watch the count and share columns — 1%~3% is a common target for focus keywords), topic analysis of articles, hot-word extraction from comments, and comparing writing styles.
How to use
- Paste the text you want to analyze into the box above.
- Adjust stop words, minimum length and scope, then click "Analyze".
- Review the ranking, then copy it as text or export it as CSV for Excel.
FAQ
Is the Chinese segmentation accurate?
It uses dictionary-based forward maximum matching, which handles common vocabulary well. Rare proper nouns may be split into single characters — replace such words with spaces around them if you need exact counts. It is reliable for frequency statistics, not for syntax-level tasks.
Which stop words are included?
About 300 Chinese function words (的、了、着、和、是…) and 100+ English stop words (the, a, of, and…), covering the vast majority of meaningless high-frequency words.
How do I read SEO keyword density?
Check the count and share columns for your focus keyword: share is its frequency among all tokens. A density of 1%~3% is a common recommendation — much higher risks keyword stuffing.
Is my text uploaded?
No. Segmentation and counting run locally in your browser, and the dictionary is embedded in the page script — the analysis makes no network requests.