It doesn't pay to live in the past, at least not according to a study published recently in the journal Nature. A group of academics hailing from Massachusetts, London and Switzerland recently analyzed Google search queries and found a significant correlation between populations that search on time periods in the future and national gross domestic product. The study considered the future orientation index for 45 countries, plotting the number of searches that included one year in the future versus those that included one year in the past. Using that analysis, the researchers discovered that countries with a higher future-to-past ratio tended also to be countries with a higher GDP.
From the study:
The analysis described here shows that the value of this [future orientation] index for 45 countries in 2010 is correlated with a key economic indicator, per capita GDP. Our results are consistent with the intriguing possibility that there is a relationship between the economic success of a country and the information seeking behaviour of its citizens online.
There are a variety of factors that could impact why different populations search on years in the future versus years in the past. Perhaps people focus on the past more when Internet connectivity is relatively new because it’s the first time they have access to mass quantities of historical data. Or perhaps countries with longer histories search more frequently on the past.
The study authors have their own theories:
Firstly, these findings may reflect international differences in attention to the future and the past, where a focus on the future supports economic success. Secondly, these findings may reflect international differences in the type of information sought online, perhaps due to economic influences on available Internet infrastructure.
Whatever the reason for the correlation, the research here suggests there may be other variable comparisons possible that align search behavior with the national attributes of different populations. And the more access we have to big public data, the more we’ll be able to see where those relationships exist, and maybe even what they mean.