Print Text Statistics
Map document structure via word, sentence, and paragraph counts. Parse large datasets using UTF-8 standards to normalize content for precise editing.
Please configure parameters and execute the action.
About Print Text Statistics
Analyze text and print comprehensive statistical information. Choose which sections to include: general statistics (length, entropy, fake text detection), word statistics (counts, word set, frequency), and character statistics (counts by type, character set, frequency). Useful for text analysis, readability checks, and content auditing.
Features
The Print Text Statistics tool provides:
- General Statistics - Text length in characters, words, lines, sentences, paragraphs; Shannon entropy; fake character detection.
- Word Statistics - Total and unique word counts; words classified by category; full word frequency list.
- Character Statistics - Counts of letters, digits, whitespace, vowels, consonants; characters by category; full character frequency.
- Selectable Sections - Include only the statistics you need.
- Copy-Friendly Report - Copy the full report for use elsewhere.
Examples
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Full Report
Paste any text and check all three sections to get a complete statistical report.
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Word and Character Only
Uncheck General Statistics to get only word and character statistics.
Real-World Usage Scenarios
- Cybersecurity - Homoglyph Attack Detection - Identify visually similar characters (homoglyphs) used in phishing attempts. By analyzing the 'Fake Text Status,' security analysts can detect characters from different scripts, such as Cyrillic or Greek letters, that impersonate standard Latin characters to trick users in URLs or emails.
- SEO Content Auditing - Frequency Analysis - Optimize keyword density and avoid over-optimization by reviewing the full word frequency report. This helps editorial teams identify repetitive phrasing and ensure that unique vocabulary is used to maintain high-quality content standards for search engines.
- Linguistic Research - Complexity Assessment - Evaluate the informational density of a document using the Shannon entropy score. Academics and linguists use this metric to determine the predictability and complexity of a text, distinguishing between technical academic writing and simplified marketing copy.
- Technical Writing - Layout and Constraints - Ensure technical documentation fits specific UI or platform constraints by monitoring character-to-word ratios and sentence length. The tool helps writers stay within precise limits for metadata, social media snippets, or software interface labels.
Frequently Asked Questions
What does 'Text Entropy' represent in the report?
Text entropy, specifically Shannon entropy, measures the unpredictability and information density of the characters in your text. Higher values indicate a more diverse and complex character set, while lower values suggest repetitive or highly structured patterns.
How does the 'Fake Text Status' identify suspicious characters?
It scans for homoglyphs and full-width characters. These are characters that look identical to standard letters but belong to different Unicode blocks (like a Cyrillic 'а' vs. a Latin 'a'). Detecting these is critical for spotting phishing or character-based evasion tactics.
Why are words categorized by character length (e.g., 1-3, 4-6 chars)?
Categorizing words by length helps in assessing readability. A high frequency of long words (11+ characters) may indicate a complex or academic tone, while a high percentage of short words often suggests simpler, more accessible communication.
Can this tool help with keyword stuffing detection?
Yes. The 'Full Word Frequency' section lists the most used words. If your target keywords appear with an unnaturally high frequency compared to other terms, it serves as a signal to diversify your language to avoid SEO penalties.
