The award was announced at the NetMob Conference in Massachusetts Institute of Technology on May 1.

“I’ve been thinking about mathematical aspects of political conflict for a couple of years,” Meyer said in a UCSD News Center release. “Civil war results from this. Understanding how civil wars spread relies on understanding social divisions.”

The research was conducted in conjunction with the UC Institute on Global Conflict and Cooperation. Meyer’s team used one of four data sets provided by France Telecom Orange to mathematically measure interactions through a volume of cell phone calls, determining if clustering a telecommunications network could inform them about language or ethnic groups in countries.

“France Telecom Orange’s subsidiary in Cote d’Ivoire provided four separate mobile telecommunications datasets based upon 2.5 billion calls and short message service exchanges between customers over the 150 day period of Dec. 1, 2011 to April 28, 2012 — which is an example of ‘big data,’” Meyer said. “They also provided the geolocations of 1238 cell antennae within the country. We analyzed one of the datasets, which provided the call volume between each pair of antennae for each hour in the time period.”

In the first stage of research, Meyer and his team theorized that the number of the calls formed geographical antennae partitions, or communities. They discovered that the two partitions have a strong association even after accounting those between two locations would be proportional to the product of the total calls made at each location, divided by some power of the distance between them. According to Meyer, this finding indicates that there is a close correlation between the number of calls and proximity of call locations — thus, there will be more calls when the two locations are closer together.

In the second stage, the research team grouped together antennae that had more calls between them and compared the grouped data to antennae in different groups. These groups were seen to be geographically connected as well.

“When we compared the resulting partition of Cote d’Ivoire into regions, we found that it appeared to align closely with a partition of the country by local majority language,” Meyer said.

Meyer and his team hopes to use the gathered telecommunications data to better understand language communities and estimate mathematical associations between geographical divisions.