Text Statistics Analyzer — Free HTML CSS JS Snippet

Word processors bury character and word counts behind a menu, and most standalone "word counter" tools stop there. This snippet computes a fuller picture of a piece of text — word, character, sentence, and paragraph counts, average sentence length, estimated reading and speaking time, and the most frequent non-trivial words — entirely with regular expressions and array operations, updating on every keystroke.

Counting words without miscounting punctuation

Rather than splitting on whitespace (which would count a lone hyphen or ellipsis as a word), the tool matches the text against /[A-Za-z0-9']+/g — a sequence of letters, digits, or apostrophes. This correctly counts don't as one word rather than two, while punctuation-only fragments and stray symbols are never counted, which is closer to how a human would count words by hand than a naive whitespace split.

Detecting sentence boundaries with a fallback for the last sentence

Sentence counting matches runs of non-terminator characters followed by one or more ., !, or ? characters, with a second alternative in the same pattern ([^.!?]+$) to catch trailing text that never received a closing punctuation mark. Without that fallback, a piece of text ending mid-thought without a period would silently lose its last sentence from the count — a small detail that matters most for text still being drafted, which is exactly when a live word-count tool gets used.

Splitting paragraphs on blank lines, not just newlines

Paragraphs are detected by splitting on /\n\s*\n/ — one or more blank lines — rather than every single newline, since a single line break inside a paragraph (a soft wrap) should not itself start a new paragraph. Each resulting chunk is trimmed and empty chunks are discarded, so trailing blank lines at the end of the text do not inflate the count.

Estimating reading and speaking time from established rates

Reading time uses 200 words per minute, a commonly cited average adult silent-reading speed; speaking time uses roughly 130 words per minute, closer to a natural conversational speaking pace. Both are simple divisions of the word count by these rates, then formatted by formatTime() into a compact "Xm Ys" string, or just seconds for anything under a minute — useful for sanity-checking whether a video script or presentation script actually fits its intended time slot.

Building a stop-word-filtered frequency list

wordFrequency() lowercases every word, skips a small built-in list of common English stop words (the, a, of, and, and similar) along with single-character tokens, and tallies the rest in a Map. The resulting entries are sorted by count descending and the top eight are rendered as horizontal bars scaled relative to the most frequent word — surfacing the words a piece of writing actually leans on, rather than being dominated by function words that appear in every English sentence regardless of topic.