As you consume the news each day, you get a general sense of what the big stories are. If CNN is leading the hour with news about the Supreme Court, you open the newspaper to find a story about the Supreme Court on the front page, and then you spot a Supreme Court story at the top of Yahoo! News, you can bet the Supreme Court is the hot topic. But this general way of identifying a hot topic isn't as precise as actually analyzing the content itself to quantify which keywords are mentioned most often throughout a day.

With digital information, it's possible to track exactly which words are used more frequently than others. And there are a number of ways you can categorize information to make that tracking easier. One system of categorization is called tagging, in which people add keywords to an article, photo, or web site in order to organize that bit of information. Each keyword is referred to as a tag, and lots of fun can be had analyzing the tags.

A popular way to visualize tag usage is in the form of a tag map that displays more popular tags in a larger font. So popular tags appear large, and less-popular tags appear small. With one glance at a tag map, you can see which topics are hot.

Now, imagine you have a source of information, but no people to tag it for you. That's where the Yahoo! Contextual Web Service can help. This service lets you send an arbitrary amount of text, and it will automatically extract keywords from that text. The service ignores common words such as a, and, or the and returns the more unique words from a text. For example, the Yahoo! Contextual Web Service analysis of the text of this hack returned phrases such as supreme court, hot topic, and search api.

By automatically extracting keywords from text, you can create computer-generated tags and perform similar sorts of analysis on those tags.