A recent story in the Washington Post, “Want to take economy’s pulse? Try digging into Google, Twitter,” compared big data to traditional sources for statistics.

As the statistical agency responsible for many of the nation’s demographic and economic indicators, we are researching the use of big data from publicly available sources to enhance our traditional methods of gathering official statistics. In 2011, the National Science Foundation and the Census Bureau came together to fund discovery and innovation concerning measurement in the social and economic sciences – discoveries meant to match the rapid changes in today’s population and economy. This program is known as the NSF-Census Research Network or NCRN.

NCRN-funded research by Matthew Shapiro of the University of Michigan has shown that information from Twitter tracks job loss trends in real time. As the Washington Post reported, Shapiro and his colleagues “scoured more than 19 billion tweets over two years for references to unemployment, hunting for phrases such as “axed,” “pink slip” and “downsized.”

The NCRN program is just one example of the Census Bureau’s commitment to leverage advances in technology and social media to reduce cost to the public while maintaining high standards of data accuracy and quality. As the costs of traditional forms of data collection continue to rise, encouraging research that makes sense of big data sources is one avenue the Census Bureau is pursuing.

Research like the University of Michigan NCRN node may present new directions for statistical agencies by tapping into information that individuals, households and businesses create in the normal course of the day. Ultimately, it may be possible to collect more timely data at higher frequency, greater precision and lower costs.