HubTools

Word Frequency Counter

Analyze word frequency and find the most common words in text.

What is Word Frequency Analysis?

Word frequency analysis is one of the oldest techniques in computational linguistics — counting how many times each unique word appears in a text and ranking them. The technique drives a wide range of applications: search-engine indexing (TF-IDF for relevance scoring), authorship attribution (function-word frequencies are a fingerprint), readability analysis, vocabulary learning, content auditing, and SEO keyword density checks. The catch is that without filtering, the result is dominated by stop words like "the" and "of", which carry little information. Filtering stop words and short words surfaces the content terms that actually distinguish a piece of writing. This counter runs the analysis locally with optional filters and case-insensitive matching. Need basic word and character counts instead? Use the Word Counter. Drafting content? Estimate the read time with the Reading Time Calculator.
Word Frequency Counter

How to use this tool

  1. 1
    Paste your text
    Drop the article, transcript, or document into the input. The longer the text, the more meaningful the frequency distribution.
  2. 2
    Toggle stop words and minimum length
    Filter out the most common function words and ignore words shorter than your threshold to focus on content terms.
  3. 3
    Read the ranked table
    Words appear ranked by count, with raw count and percentage. Sort by either to spot patterns.
  4. 4
    Export to CSV
    Click Export to download the ranked list as CSV for spreadsheet analysis or content-strategy reporting.

Frequently asked questions

What's the difference between a word counter and a word frequency counter?
A word counter tells you the total number of words in a text — one number, useful for length targets. A word frequency counter tells you how many times each unique word appears — a ranked distribution, useful for SEO keyword analysis, vocabulary diversity studies, content audits, and detecting overused phrases. The two answer different questions.