In the time it takes you to read this sentence, more than a thousand tweets will have been twittered and dozens of blogs posted. Much of their content will be ephemeral fluff: personal gripes and tittle-tattle interesting to no one but the parties concerned. Yet despite this, it is possible to use that torrent of information to make predictions about social and economic trends that affect us all.
Interest in the idea of analysing web data to make predictions took off around a year ago, when researchers at Google used the frequency of certain search terms to forecast the sales of homes, cars and other products.
In their landmark study, Hal Varian, Google's chief economist, and his colleague Hyunyoung Choi showed how the volume of searches for certain products, such as types of car, rose and fell in line with monthly sales. Google keeps extensive records of what is being searched for, and that information is available almost instantaneously. That could make Varian and Choi's method a far quicker way of gauging purchasing behaviour than traditional sales forecasts, which are often made by looking back at purchasing patterns.
See more at http://www.newscientist.com/article/mg20627655.800-blogs-and-tweets...