Word Counter & Analyzer

A word counter analyzes text to provide detailed statistics including word count, character count (with and without spaces), sentence count, paragraph count, and estimated reading and speaking times. Writers use word counters to meet article length requirements, students check essay word limits, social media managers verify post length constraints, and SEO professionals ensure content meets recommended length targets for search ranking. This tool goes beyond simple counting — it provides a full breakdown of your text analytics including average word length, average sentence length, and top keyword frequency. The reading time estimate uses the standard adult reading speed of 200-250 words per minute, while speaking time uses approximately 130 words per minute for presentations. All analysis happens instantly in your browser using JavaScript string operations. Your text is never stored, logged, or transmitted to any server — making this tool safe for analyzing confidential documents, legal texts, academic papers, or any sensitive content.

The word counter uses a series of JavaScript string operations to parse and analyze your input. Word counting splits the text by whitespace boundaries using a regular expression that handles multiple consecutive spaces, tabs, and newlines correctly. Character counting uses the native JavaScript string length property, with a separate count excluding whitespace characters. Sentence detection looks for terminal punctuation marks (periods, exclamation marks, question marks) while accounting for common abbreviations like Mr., Dr., and U.S. that contain periods but do not end sentences. Paragraph counting splits on double newlines or blank lines. The keyword frequency analysis tokenizes the text into individual words, normalizes them to lowercase, filters out common stop words (the, a, is, and, etc.), and then counts occurrences using a JavaScript Map data structure. Results are sorted by frequency and displayed as a ranked list. All of these operations use native JavaScript string methods and regular expressions — no external NLP libraries or API calls are needed, and processing is instantaneous even for texts exceeding 100,000 words.