Companies, organizations, and university research groups already dip into public and personal data to learn more about us. Now, the U.S. government agency DARPA (Defense Advanced Research Projects Agency) has announced a new program that aims to exploit our web-obsessed world, called Next Generation Social Science or NGS2 for short, and it’s on the hunt for new forms of data-mining and emerging technologies for social science research.

Social studies — including studies on culture, economics, anthropology, and psychology — are often limited by research subject access. For instance, most of the research at universities end up culling data from college-aged students, which wouldn’t be that useful for a group studying how computers and tablets affect preschoolers’ handwriting abilities. Large studies end up becoming an individual case study.

DARPA program manager, Adam Russell, further explains that because of research limitations and the unpredictable, complex variability between humans, it’s hard to make the shift from merely making relationships to establishing concrete causations.

“Physicists have joked about how much more difficult their field would be if atoms or electrons had personalities, but that’s exactly the situation faced by social scientists,” Russell says about the project.

Online data gives researchers access to thousands of diverse volunteer subjects. But DARPA is searching for sophisticated, reproducible methods to use and collect public datasets like global online gaming and alternate reality platforms.

NGS2 will initially back researchers developing tools that identify causal mechanisms of “collective identity” formation, which observes how individuals form groups, and how the community breaks down after placing the group under different circumstances, CHIPS magazine reports. DARPA is holding a day for research groups to pitch their ideas for funding on March 22 in Arlington, Virginia. Here are the three core social study elements NGS2 supports:

  1. Predictive modeling and hypothesis generation
  2. Innovative experimental methods and platforms
  3. Interpretation and reproducibility of research results.
Photos via James Cridland/Flickr