Award-winning film uses math to provide ‘poetical vision’ of Earth’s complexities

Excerpt from “Network Earth,” a film created by Northeastern data visualizer Mauro Martino in collaboration with a research team led by Albert-László Barabási, Robert Gray Dodge Professor of Network Science. It depicts breakthrough research describing a statistical tool they developed to identify a network’s “tipping point.”

“To live on Earth is to be part of a network, a giant web where almost every creature depends on others for survival.”

So begins the short film Network Earth, created by Northeastern data visualizer Mauro Martino in collaboration with a research team led by Albert-László Barabási, Robert Gray Dodge Professor of Network Science and University Distinguished Professor of Physics. The film was recently named the Expert’s Choice video winner of the 2017 Vizzies Challenge, a competition sponsored by Popular Science in partnership with the National Science Foundation to recognize, as the NSF puts it, “exemplars of information made beautiful.”

Network Earth was created to accompany the Northeastern researchers’ breakthrough Nature paper describing a statistical tool they developed to identify a network’s “tipping point,” that is, the point where the system’s “resilience”—its ability to adjust to disturbances in order to remain functional—gives way to collapse.


“In the film I have tried to represent a poetical vision of the complexity of our planet via mathematics,” said Martino, professor of the practice in the College of Arts, Media and Design.

That it does, with eloquent depictions of ecosystems as networks, animated construction of the interrelationship between nodes and links, and astute commentary on topics such as the disappearance of honeybees and unexpected crashes in commercial fisheries.

“The failure of a complex system can lead to serious consequences, whether to the environment, economy, human health, or technology,” said Barabási. “But there was no theory that considered the many parameters and components underlying such systems, making it difficult, if not impossible, to predict the systems’ resilience.”

With the researchers’ findings, now there is.