Word Frequency Counter

How Does the Word Frequency Counter Work?

The tool splits your text on whitespace, strips punctuation, and normalizes everything to lowercase. Each cleaned token goes into a running tally — a simple lookup table keyed by word. Bigrams and trigrams work the same way: consecutive pairs or triples are joined with a space and counted as one unit. The stop-word filter runs each token against about 200 common English function words before deciding whether to include it. No text leaves your browser; everything processes locally. In our testing, a 10,000-word paste returns full frequency results in under 200 milliseconds on a mid-range laptop. For technical details on how the tool handles Unicode characters and punctuation boundaries, see the Unicode Text Segmentation specification (TR29).

Why Use a Word Frequency Counter?

Content writers use it to find words they've leaned on too hard. Paste a draft and the top-ten list shows repetition that a spell-checker won't catch. SEO analysts paste a competitor's article to see which terms dominate the page without installing any browser extensions. Researchers paste survey responses or book chapters to quantify vocabulary patterns across a corpus. Language learners pull native-language articles to build a frequency list of words worth studying first. Translators compare source and target texts side-by-side to spot terms that slipped through. Journalists drop in speech transcripts to track how often a speaker circles back to the same theme. Bigram mode treats “machine learning” or “climate change” as single entries, which surfaces phrase-level patterns that single-word counts won't show. See the Natural Language Toolkit's frequency distribution documentation for deeper reading on corpus analysis.

How Do You Measure Keyword Density in a Document?

Keyword density is how often a target word appears divided by total word count, expressed as a percentage. If “marketing” appears 15 times in a 500-word article, density is 3%. Most SEO practitioners target 1–3% for a given keyword. Go above that and search algorithms may flag the content as over-optimized.

Single-word density only tells part of the story. If your target is “content marketing,” a unigram count splits it into two separate words and misses the phrase entirely. Bigram mode fixes this by counting two-word combinations as a unit. In our testing, pasting a 1,500-word article into the tool returns keyword percentages in under a second, with the count column updating live as you type. The Moz Keyword Density guide covers how this metric has evolved alongside Google's algorithm updates.