String & Text Analyzer

What Is a Text Analyzer?

A text analyzer (also called a string analyzer or word counter) measures the statistical properties of a block of text. Developers use it to validate input lengths, writers use it to hit word count targets, and SEO professionals use it to assess keyword density and readability.

This tool processes everything locally in your browser — your text never leaves your device.

Key Metrics Explained

Character Count

Character count comes in two flavors:

• With spaces — total number of characters including whitespace. This is what the string .length property returns in most programming languages.
• Without spaces — total non-whitespace characters. Useful for platform limits that ignore spaces (some APIs, database columns).

Example:

"Hello, World!"
With spaces:    13 characters
Without spaces: 12 characters (the comma and exclamation mark are counted)

Word Count

Words are extracted as sequences of Unicode letters and digits, optionally joined by apostrophes or hyphens (for contractions like don’t and hyphenated words like well-known). Punctuation is stripped so "hello," and "hello" both count as one word.

This matches how Microsoft Word, Google Docs, and most online word counters report word count.

Line Count

Lines are counted by splitting on newline characters (\n). A single-line text returns 1. An empty string returns 0.

Sentence Count

Sentences are detected by looking for terminal punctuation (., !, ?) followed by whitespace or end of text. Most standard prose is counted accurately, though text with many abbreviations (Dr., etc.) may be slightly off — this is a known limitation shared by all text-based sentence detectors.

Paragraph Count

Paragraphs are blocks of text separated by one or more blank lines (double newlines). Empty-line separators are the universal convention in plain text, Markdown, and most document formats.

Byte Size (UTF-8)

Every string occupies a certain number of bytes when stored or transmitted. The exact count depends on the character encoding. This tool reports the UTF-8 byte size, which is the standard encoding for the web and most modern systems.

Why it matters:

• Database columns: VARCHAR(255) in MySQL limits bytes, not characters. A 255-character string with CJK chars may exceed the limit.
• API payloads: HTTP bodies are measured in bytes; JWT tokens have practical size limits.
• SMS: Standard SMS is 160 7-bit characters (140 bytes). Unicode SMS drops to 70 characters per segment.

Reading Time and Speaking Time

Reading Time (238 WPM)

Reading time is estimated at 238 words per minute — the average silent reading speed for adults, based on the landmark 2019 study by Brysbaert (Reading Research Quarterly). For reference:

Speaking Time (130 WPM)

Speaking time is estimated at 130 words per minute — a comfortable conversational pace that matches typical podcast hosts, teachers, and presentation speakers. Fast speakers may reach 160–180 WPM; a slow, deliberate pace can drop to 100–110 WPM.

Word Frequency and Keyword Density

Top 10 Most Frequent Words

The tool counts every word (case-insensitive) and ranks them by frequency. This immediately reveals which words dominate your text.

Uses:

• Content writers: Spot unintentional word repetition before publishing.
• Developers: Analyze log files, config values, or generated content.
• SEO: Confirm your target keywords appear at the right frequency.

Keyword Density

Keyword density = (word occurrences ÷ total words) × 100%.

SEO guidelines:

• Target keyword density: 1–3% for primary keywords.
• Below 0.5%: The keyword may not register as topically relevant.
• Above 5%: Risk of keyword stuffing penalty (Google Panda, Penguin algorithms).

For a 1,000-word article, a 2% keyword density means the keyword appears ~20 times.

Character Frequency Distribution

The character frequency chart shows the relative frequency of each letter and digit in your text (case-insensitive). The bar height is proportional to count, normalized to the most frequent character.

Typical English text distribution (approximate):

If your text’s distribution looks very different, it may indicate technical content, non-English text, or a deliberate stylistic choice (like a lipogram).

Common Use Cases

For Developers

• Input validation: Check that user-submitted text fits within a database VARCHAR column, API field limit, or UI constraint.
• Log file analysis: Paste a log excerpt to quickly count error occurrences or identify the most frequent log terms.
• String length debugging: Compare character count vs. byte size to diagnose encoding issues in multi-byte character handling.
• Content generation testing: Measure the output of AI-generated text to verify word count targets are met.

For Writers and Content Creators

• Hit word count targets: Know exactly when you reach 500, 1,000, or 5,000 words.
• Readability planning: Use reading time estimates to gauge how long a blog post, email, or newsletter will take to read.
• Detect repetition: The top word frequency list reveals repeated filler words (very, really, just) before you publish.
• Platform compliance: Check character limits for Twitter (280), LinkedIn posts (3,000), meta descriptions (155–165), and title tags (50–60).

For SEO Professionals

• Keyword density audit: Verify that target keywords appear at the optimal frequency for on-page SEO.
• Meta tag length: Count the exact characters in <title> and <meta description> before implementation.
• Content length benchmarking: Compare your article’s word count against top-ranking competitors to gauge content depth expectations.
• Readability scoring: Use sentence and paragraph counts as inputs for manual Flesch-Kincaid or Gunning Fog Index calculations.

String Analyzers vs. Word Processors

Frequently Asked Questions

Does this tool work offline?

Yes. Once the page loads, all analysis runs locally in your browser with no internet connection required.

Is there a text size limit?

There is no hard limit imposed by the tool. In practice, browsers can handle tens of megabytes of text without performance issues. Very large texts (10+ MB) may cause a brief calculation delay on slower devices.

Why does my word count differ from Microsoft Word?

Word processors differ slightly in how they handle edge cases like hyphenated compounds, em dashes, and non-breaking spaces. The difference is typically 0–2 words for standard English prose. Both approaches are valid — they just define “word” slightly differently.

Can I analyze code or technical strings?

Absolutely. The character and byte counters work on any UTF-8 string, including JSON, SQL, regex patterns, Base64-encoded strings, or code snippets. The word counter may produce lower counts for highly technical strings with few dictionary words.

How do I use this for accessibility compliance?

Reading time estimates help ensure content is not overwhelming for users with cognitive disabilities. Paragraph count assists in breaking up dense text. For formal accessibility testing, combine this tool with dedicated readability scorers (Flesch-Kincaid, Hemingway Editor).