Word Cloud
Larger = more frequent. Click to highlight in table.Frequency Table
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Word
Count
% of total
Uses of Word Frequency Analysis
Also searched as: word frequency counter free | word frequency analyzer | most common words in text | word cloud generator
Word frequency analysis has wide applications: SEO content auditing (finding over-used or missing keywords), academic text analysis, plagiarism detection, readability improvement, historical corpus analysis, and natural language processing training data. Zipf's Law, discovered by linguist George Zipf in 1935, states that in any language corpus the most common word appears roughly twice as often as the second most common, three times as often as the third, and so on — a pattern that holds remarkably consistently across all human languages.
Use the Word Frequency Counter above — enter your values and get instant results. This free online tool calculates how to count word frequency without any download or signup required. Results update in real time as you type.
Use the Word Frequency Counter above — enter your values and get instant results. This free online tool calculates word frequency analysis free without any download or signup required. Results update in real time as you type.
Word frequency analysis is used for: SEO content analysis (checking keyword density and finding over-used or missing terms). Academic research (determining vocabulary size, comparing texts, identifying authorship). Historical linguistics (tracking how language changes over centuries). Plagiarism detection (comparing word distribution signatures). Natural language processing (building language models and training classifiers). UX writing (ensuring key terms appear frequently enough for clarity). Cipher breaking in cryptography (frequency analysis is the basis for breaking simple substitution ciphers).
Stopwords are extremely common words (the, a, an, is, are, in, on, at, to, for, of, and, or, but, etc.) that appear in virtually every text and provide no meaningful content signal. In any English text, 50–60% of words are typically stopwords. Removing them reveals the meaningful content words — nouns, verbs, adjectives — that actually characterise the text. Different NLP applications use different stopword lists. This tool uses a curated list of ~150 common English stopwords while keeping meaningful short words like 'seo', 'api', 'tax', etc.
Zipf's Law states that in any large natural-language corpus, word frequency is inversely proportional to rank. The most common word appears approximately twice as often as the second most common, three times as often as the third, and so on. In English: 'the' is the most common word (~7% of all words). 'of' is second (~3.5%). 'and' is third (~3%). This power law holds remarkably consistently across all studied human languages, many programming languages, city population sizes, income distributions, and website traffic patterns.
Copy the full text of your article and the top-ranking competitor articles into this tool separately. Compare the most frequent content words (after removing stopwords). Gaps show topics your article covers less thoroughly. If competitors frequently use terms you don't mention, those represent missed semantic coverage. This is a simplified version of what tools like Clearscope and MarketMuse do — they run frequency analysis on top-ranking pages to identify which terms Google considers topically relevant for a given query.
Word frequency is the raw count and percentage of each word. Keyword density (as shown in the Keyword Density Analyzer tool) focuses on 1-gram, 2-gram, and 3-gram phrases in relation to total words, and is specifically an SEO metric for tracking a target keyword. Word frequency is a broader linguistic analysis tool. For SEO use the Keyword Density Analyzer; for general text analysis, vocabulary research, or content auditing, word frequency gives a more complete picture of what your text is actually about.