This blew me away. I have used Google trends once in a while. But Google Flu Trends describes a really innovative application of search data and trends to predict the spreading of Flu in USA. Watch the animation as well.
Each week, millions of users around the world search for online health information. As you might expect, there are more flu-related searches during flu season, more allergy-related searches during allergy season, and more sunburn-related searches during the summer. You can explore all of these phenomena using Google Trends. But can search query trends provide an accurate, reliable model of real-world phenomena?
We have found a close relationship between how many people search for flu-related topics and how many people actually have flu symptoms. Of course, not every person who searches for “flu” is actually sick, but a pattern emerges when all the flu-related search queries from each state and region are added together. We compared our query counts with data from a surveillance system managed by the U.S. Centers for Disease Control and Prevention (CDC) and discovered that some search queries tend to be popular exactly when flu season is happening. By counting how often we see these search queries, we can estimate how much flu is circulating in various regions of the United States.
If you can do this with search data from one search engine, imagine what you can do with actions that follow search (even though most of that may not be available to Google and other search engines). What if all the searches and clicks are anonymized into statistical data and consolidated into one global (open) linked data?
- Percolation of News? (tracking news items search and clicks on news articles)
- Spread of product/service awareness? (searches following advertisements in different medias)
- Trends in economic activity from distributed data instead of just looking at the major market indicators?
I would certainly love to know when the economic activity is stabilizing or up trending so that I can get some leading indicators.
It is interesting to note that this analysis is from Google.org. Does that mean other non-profits can get access to this data?