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How your online footprint preditcs the future

Published by under AI / CI / Computing,News categories on May 22, 2009

slide showing main used web utilities as Facebook Real time web search like Twitter messages, can give a clue of what people around the world are thinking or doing at any moment. The latest research from Google, suggests that online footprint including real time results could be even more powerful: they may reveal the future as well as the present.

Google researchers Hyunyoung Choi and Hal Varian combined data from Google Trends with models used by economists to predict trends in areas such as travel and home sales. The result is better forecast in almost every case.

Projected sales of cars and vehicle parts, for example, can be extrapolated from the figures for the previous month and form last year at this time, but adding in the volume of automobile related search queries to the model cut the error rate by 15%.

This also mean to improve accuracy of early warning, and it works because searches reveal something about people’s intentions. For example, Varian suggests a surge in people using the term “unemployment insurance” may help predict looming economic problems.

Google has demonstrated before that search data can predict flu outbreaks, and last week World Bank economist Erik Feyen said he could cut errors in a model that forecasts lending to the private sector by 15% using Google search data.

But real time results could have even more predictive power: knowing what people are actually doing, not just thinking, at a particular instant gives a strong hint of the future consequences.

Other data is targeted more specifically towards future dates. At the FutureMe website you can send yourself an email scheduled to arrive at any date between now and 30 years hence. Johan Bollen of Los Alamos National Laboratory and Alberto Pepe of the University of California, Los Angeles, applied a mood rating system to the text from over 10,000 FutureMe emails sent in 2006 to gauge people’s hopes, fears and predictions for the future.

They found that emails directed at 2007 to 2012 were significantly more depressed in tone than messages aimed at the subsequent six years. Could they have predicted the world’s current economic Crisis?

Without more data, that is no more than an intriguing possibility. So Bollen plans to look at more FutureMe emails, as well as Twitter messages, to search for mood swings that foreshadow other economic changes. If he finds any such links, the same sources might be used to try and predict future economic fluctuations.

So will our online footprint become a central part of economic forecasting? We’ll have to wait and see, or perhaps do a quick web search.


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