![]() ![]() in tag clouds tags that apply to most of your content and so over-dominate the cloud to the point of it's being meaningless.Since the word cloud strips each word of its context, and just looks at frequency, it came out dominated by the words "like" and "policy" - a rather misleading message. Nieman in the above link recounts a time he developed a word cloud from text on US far-right 'tea party' activists' opinions of their political nemesis Barack Obama. mundane or meaningless words, like "because", for obvious reasons.If you're automatically generating one, take care to exclude: He goes a bit far: the important message is, don't take them too seriously Here's a conclusive debunking of that craze by a New York Times visualisation expert, comparing use of word clouds for analysis to "reading tea leaves". There was a deservedly mocked short-term craze of journalists using word clouds as a low-effort alternative to analysing important texts. If using them as a navigational element, remember it can be a fun bonus but it's no alternative to good well structured navigation. ![]() generous white space around the cloud, and restrained balanced colours within it They're visually interesting, but by definition cluttered and noisy, so take care to make sure they don't make the whole page too cluttered and noisy.Basically, they're all variants on the theme of "remember that you're just showing people a potentially attractive, mostly arbitrary snapshot": Here are some word cloud faux-pas to avoid. These can be a fun and attractive way to get a snapshot glimpse of what might be the rough theme across a large amount of words.īut, like anything fun and attractive that can be automatically generated, it's easy to spoil to the fun by taking it too far or executing it clumsily. For example, some blogs have automatically generated word clouds based on their tags ("tag clouds"), with the most common tags largest. Sometimes, word clouds are used as navigational elements on web sites.You get a rough sense of the similarities and differences in tone of the speeches from looking at them. For example, here's a pair of word clouds based on Barack Obama's two presidential acceptance speeches. There are tools that analyse text and generate word clouds based on the frequency of the words.Sites like Wordle allow manual weighting so you can ensure that the size of each word is appropriate.Usually in a word cloud, the sizes of the words are linked in some way to the relative importance of that word. To add a little background on word clouds. ![]()
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