Text Statistics, Entropy & Complexity Analyzer
Free online text statistics, entropy, and complexity analyzer. Measure Shannon information entropy (bits per character), Flesch Reading Ease readability scores, Gematria letter sums (A=1, Z=26), top letter frequencies, and top word distributions in real-time. 100% private, browser-based execution.
Text Statistics, Entropy & Complexity Analyzer
Analyze reading difficulty, Shannon information entropy, letter frequencies, Gematria letter sum, and vocabulary richness.
Readability Complexity (Flesch Score)
0 / 100Top 5 Most Frequent Words
Top Letter Frequencies
Step-by-Step Instructions
Paste Your Document or Manuscript
Enter your essay, article, blog post, book chapter, or transcript into the analysis editor.
Explore Comprehensive Linguistic Metrics
Review detailed statistics including total words, characters (with and without whitespace), sentences, paragraphs, syllable density, and lexical richness.
Inspect Keyword Frequency & Density
Analyze top unigram, bigram, and trigram repeating phrases and keyword density percentages to ensure natural, un-stuffed SEO optimization.
Review Time & Readability Benchmarks
Check silent reading duration, speech pacing, average sentence length, and reading difficulty scores.
Key Features & Capabilities
- In-depth lexical density analysis measuring unique word ratio (Type-Token Ratio / TTR) and vocabulary variety
- N-gram phrase frequency tracker extracting top 1-word, 2-word, and 3-word combinations with exact percentage densities
- Character distribution breakdown isolating alphabetic letters, numeric digits, punctuation marks, and whitespace bytes
- Calibrated silent reading (225-250 WPM) and speech time estimation (130-150 WPM)
- Sentence length variance analysis highlighting run-on sentences and syntactic rhythm patterns
- 100% private client-side processing ensuring academic papers and confidential manuscripts are never uploaded
Frequently Asked Questions
What is Type-Token Ratio (TTR) and lexical diversity in text analysis?
Type-Token Ratio (TTR) is the ratio of unique words (types) to the total number of words (tokens) in a text. A higher TTR indicates rich vocabulary and diverse expression, while a low TTR signals repetitive language or keyword stuffing.
How does the N-gram keyword frequency analyzer help with SEO content?
The N-gram tracker identifies 1-word, 2-word, and 3-word repeating phrases to help writers ensure their primary and secondary keywords appear at a healthy, natural frequency (typically 1% to 2.5% density) without triggering Google search spam penalties for over-optimization.
How are sentences and paragraphs tokenized?
The analyzer uses Unicode Standard Annex #29 sentence boundary segmentation algorithms, distinguishing terminal punctuation (`.`, `!`, `?`) from decimal numbers (`3.14`) and common abbreviations (`e.g.`, `Dr.`, `Inc.`), while paragraph counts are determined by consecutive newline sequences (`\n+`).
Are my draft articles and confidential documents stored on your servers?
No. All text parsing, frequency counting, and mathematical calculations execute entirely within your browser's JavaScript engine. No content is ever sent across the network.
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