There’s a great article in this week’s Nature — out this afternoon — featuring computer scientists like Cornell’s Jon Kleinberg, Harvard’s David Lazer (now at Northeastern), and Columbia’s Duncan Watts, who are leveraging today’s digital data streams (e.g., e-mail, social media, mobile devices, etc.) to transform the way we study social science. Here’s an excerpt about their pioneering efforts in computational social science:

Jon Kleinberg’s early work was not for the mathematically faint of heart. His first publication¹, in 1992, was a computer-science paper with contents as dense as its title: ‘On dynamic Voronoi diagrams and the minimum Hausdorff distance for point sets under Euclidean motion in the plane’.

 

That was before the World-Wide Web exploded across the planet, driven by millions of individual users making independent decisions about who and what to link to. And it was before Kleinberg began to study the vast array of digital by-products generated by life in the modern world, from e-mails, mobile phone calls and credit-card purchases to Internet searches and social networks. Today, as a computer scientist at Cornell University in Ithaca, New York, Kleinberg uses these data to write papers such as ‘How bad is forming your own opinion?’² and ‘You had me at hello: how phrasing affects memorability’³ — titles that would be at home in a social-science journal.

 

“I realized that computer science is not just about technology,” he explains. “It is also a human topic.”

 

Kleinberg is not alone. The emerging field of computational social science is attracting mathematically inclined scientists in ever-increasing numbers. This, in turn, is spurring the creation of academic departments and prompting companies such as the social-network giant Facebook, based in Menlo Park, California, to establish research teams to understand the structure of their networks and how information spreads across them.

 

“It’s been really transformative,” says Michael Macy, a social scientist at Cornell and one of 15 co-authors of a 2009 manifesto⁴ seeking to raise the profile of the new discipline. “We were limited before to surveys, which are retrospective, and lab experiments, which are almost always done on small numbers of college sophomores.” Now, he says, the digital data-streams promise a portrait of individual and group behaviour at unprecedented scales and levels of detail. They also offer plenty of challenges — notably privacy issues, and the problem that the data sets may not truly be reflective of the population at large.

 

Nonetheless, says Macy, “I liken the opportunities to the changes in physics brought about by the particle accelerator, and in neuroscience by functional magnetic resonance imaging.”

 

…

 

Many researchers remain unaware of the power of the new data, agrees Harvard social scientist David Lazar, lead author on the 2009 manifesto. Little data-driven work is making it into top social-science journals. And computer-science conferences that focus on social issues, such as the Conference on Weblogs and Social Media, held in Dublin in June, attract few social scientists.

 

Nonetheless, says Lazar, with landmark papers appearing in leading journals and data sets on societal-wide behaviours available for the first time, those barriers are steadily breaking down. “The changes are more in front of us than behind us,” he says.

 

Certainly that is Kleinberg’s perception. “I think of myself as a computer scientist who is interested in social questions,” he says. “But these boundaries are becoming hard to discern.”

 

Reprinted by permission from Macmillan Publishers Ltd: Nature 488, 448-450 (23 August 2012) doi:10.1038/488448a, copyright 2012.

Be sure to read the full news feature on Nature‘s website.

(Contributed by Erwin Gianchandani, CCC Director)