Many sites offer some statistics like “The hottest topics in the last 24h”. For example, Topix.com shows this in its section “News Trends”. There, you can see the topics which have the fastest growing number of mentions.
I want to compute such a “buzz” for a topic, too. How could I do this? The algorithm should weight the topics which are always hot less. The topics which normally (almost) no one mentions should be the hottest ones.
Google offers “Hot Trends”, topix.com shows “Hot Topics”, fav.or.it shows “Keyword Trends” – all these services have one thing in common: They only show you upcoming trends which are abnormally hot at the moment.
Terms like “Britney Spears”, “weather” or “Paris Hilton” won’t appear in these lists because they’re always hot and frequent. This article calls this “The Britney Spears Problem”.
My question: How can you code an algorithm or use an existing one to solve this problem? Having a list with the keywords searched in the last 24h, the algorithm should show you the 10 (for example) hottest ones.
I know, in the article above, there is some kind of algorithm mentioned. I’ve tried to code it in PHP but I don’t think that it’ll work. It just finds the majority, doesn’t it?
I hope you can help me (coding examples would be great).
