Word Cloud Designer

Generate word clouds with custom shapes, fonts, color palettes, and word frequency weighting.

Tested tool guide Tested browser tools Checked August 16, 2026

What Word Cloud Designer does, with a checked example

This tool takes text you paste in - an article, survey responses, a list of tags - or an explicit list of word:weight pairs, and turns it into a word cloud where size reflects frequency or the weight you supplied. You choose a palette, a font, and an outline shape (circle, heart, or a custom silhouette) that the words are packed into, then export the result as an image. The part people miss: plain-text mode silently drops common stop words like 'the' and 'and' before counting, so a word that looks important in your source text can vanish entirely unless you switch to explicit weight pairs.

Worked example

A concrete input and expected output from the current implementation.

Input

cat cat sat on the mat, the cat ran and the dog sat

Expected output

cat=3 (largest), sat=2 (medium), mat=1, ran=1, dog=1 (tied smallest)

Stop words 'on', 'the', and 'and' are removed before counting, leaving five content words; their raw occurrence counts in the remaining text set the relative sizes, with cat ranked largest at 3 occurrences.

How the result is produced

Frequency counting and stop-word filtering

When you paste plain text, the tool strips punctuation and tallies occurrences of each remaining token exactly as typed - capitalization is preserved, not normalized - then removes common stop words (a, an, the, and, on, etc.) before ranking words by count. Switching to word:weight pair input skips counting and stop-word removal entirely, so every entry renders at exactly the weight you assign.

Shape-constrained packing

Words are sorted by weight, largest first, and placed one at a time - spiraling outward from the center or from a masked outline you pick (circle, heart, custom silhouette) - so each new word claims the nearest open space that fits without overlapping earlier words. Because placement depends on what is already down, adding or removing even one word can shift the whole layout.

Good uses

condensing dozens of open-ended survey answers into one glance-able chart of the most repeated themes
turning a speech, mission statement, or article into a poster-style visual for a slide or printout
building a quick keyword banner for a blog post, README, or portfolio project from a list of tags

Limits and checks

word frequency treats singular/plural and different capitalizations as separate words unless you normalize them first, so 'Cat', 'cat', and 'cats' can each show up as their own smaller entry instead of one combined larger one
the built-in stop-word list removes common function words automatically in text mode; if a short but meaningful word (an acronym, for instance) gets swept up in that list, the only fix is switching to explicit word:weight input
packing is layout-dependent, not purely frequency-driven - words are placed in strict descending-weight order, but the outline shape constrains where open space remains by the time a low-count word's turn comes, so a low-count word can still land near the center if that's where the last open gap happens to be, especially inside a thin or irregular custom silhouette; position in the finished cloud is not a reliable proxy for rank

Common questions

Why did some of my words disappear from the cloud?

Most likely they were filtered out as stop words (the, and, on, etc.) during plain-text counting, or they were too low-weight to fit the remaining space inside your chosen shape at a legible size. Switch to word:weight input to force specific words to appear regardless of the stop-word list.

Will the same input always produce the same layout?

Not confirmed to be deterministic - packing places the highest-weight word first and fits each following word into the nearest open space, so a small change to the word list, shape, or font can shift positions. Treat each export as final rather than expecting to reproduce an exact layout later.

References and verification

The example and behavioral notes were checked against the browser implementation. Standards and primary references below define the relevant format, formula, or platform behavior.