We can also take this list and put the names in alphabetical order, which is often done for tag clouds. In this format it's easier to see other aspects of the top 50 queried color names, such as the popularity of crimson in that both "crimson" and "crimson red" are in the list.

This query cloud can also be sorted by the corresponding hue angle as well. In this case the corresponding RGB values were assumed to sRGB and converted to CIELAB hue values and then sorted. In this format it makes it easier to see overall trends in the color name queries by hue. For instance, there appear to be a lot more queries for reds and blues than there are for yellows and greens.

Backing up a little bit for some discussion, I can hear someone out there asking "why do your names line up like they are in a table?" That's because I put them in an HTML table. Flowing text is cool from a typographical point of view but for 50 color names a basic table looks pretty clear to me as well (flame me and I'll do an on-line comparison).

I can also hear someone else out there asking "what's a query cloud?" OK so there is no wikipedia article about 'query cloud' and Googling(tm) 'query cloud' only gives 169 not very helpful results. A query cloud is a cloud of queries. There has been some good discussion online about 'tag clouds' being just one instance of a more specific type of 'text cloud'. I'm just being specific that the above are 'query clouds' and not 'tag clouds'.

And I can hear yet another person out there asking "why didn't you add links so that we could click through from the query cloud back to the specific color thesaurus entry?" Fair question. One reason is I don't want to spend that much time on this post. The second reason is I don't want to bias the top 50 list by having all the stats thrown off by users of the color thesaurus and click-throughs from the zeitgeist post. Besides this post is more about color and lexical visualization than pushing the color thesaurus.

Now for the lexical clouds dicussion. Previously I linked to a blog post that went on about text clouds but now I'm using the term lexical cloud. That's because I think text cloud is still too narrow and have my doubts about how useful the technique is for a text or literary work. That is I'm not sure how much you get out of applying text clouds to longer pieces of fiction or non-fiction to condense or visualize the results. But as a general lexical or word-based or name-based technique I think it could be quite useful. For example anything with a label or name and one or more associated metrics or meaures can make good use of lexical clouds. Consider the current standings for American football where the team name is listed and the current percentage of wins is used to scale the names:

Pretty easy to read I think. Unlike the officially tabulated data there are no three decimal places of precision to wade through. It's easy to see the top three and bottom three teams at a glance. This data could also be sorted alphabetically as was done above or could be sorted by conferences and divisions.

Reading across rows then it is also easy to see which teams are in stronger or weaker divisions. It is also easy to look at the second column to see which second place teams are strong in their divisions. Finally, since I'm a color guy it's possible to color code the recent wining or losing streaks by team. In this way teams with longer recent winning streaks are coded red and teams with longer losing streaks are blue. Think hot or cold.

Having created this lexical cloud I'm really curious now to see how the Jaguars do with the rest of their season. All without numbers. And not a tag or query or book chapter in sight.