Word Frequency Counter

Keyword density is the percentage of times a keyword appears in a text relative to the total word count: (keyword count / total words) × 100. SEO conventionally aimed for 1-3% density, but modern search engines do not rely on simple density metrics. Keyword stuffing — artificially inflating density — is a spam signal. Focus on natural usage and topical relevance instead.

Stop words are common function words that carry little semantic meaning on their own — articles (the, a, an), prepositions (in, on, at), conjunctions (and, but, or), and auxiliary verbs (is, are, was). They are filtered out in search indexing and text analysis to focus on content words. The exact stop word list varies by application and language; this tool uses a common English set.

Zipf's law states that in natural language, the frequency of any word is roughly inversely proportional to its rank in frequency. The most common word appears twice as often as the second most common, three times as often as the third, and so on. This means a few words dominate, and most words are rare. After filtering stop words, the remaining distribution still follows a rough power law.

Paste your page content, enable stop word filtering, and look at the top 10-20 words. Your target keywords should appear naturally. If your primary keyword appears 0 times, consider adding it. If it appears with density above 3-4%, it may read unnaturally. Check variations and related terms — search engines understand semantic relationships, not just exact-match repetition.

TF-IDF (Term Frequency–Inverse Document Frequency) improves on raw frequency by weighing how common a term is across many documents. A word that appears often in a document but rarely elsewhere gets a high TF-IDF score — it is likely important to that document. Words that appear everywhere (like "the") get a low score even if frequent. TF-IDF is foundational to search engine ranking and text classification.