From Harvard Magazine:
If a campaign volunteer shows up at your door, urging you to vote in an upcoming election, you are 10 percent more likely to go to the polls—and others in your household are 6 percent more likely to vote. When you try to recall an unfamiliar word, the likelihood you’ll remember it depends partly on its position in a network of words that sound similar. And when a cell in your body develops a cancerous mutation, its daughter cells will carry that mutation; whether you get cancer depends largely on that cell’s position in the network of cellular reproduction.
However unrelated these phenomena may seem, a single scholarly field has helped illuminate all of them. The study of networks can illustrate how viruses, opinions, and news spread from person to person—and can make it possible to track the spread of obesity, suicide, and back pain. Network science points toward tools for predicting stock-price trends, designing transportation systems, and detecting cancer. It used to be that sociologists studied networks of people, while physicists and computer scientists studied different kinds of networks in their own fields. But as social scientists sought to understand larger, more sophisticated networks, they looked to physics for methods suited to this complexity. And it is a two-way street: network science “is one of the rare areas where you see physicists and molecular biologists respectfully citing the work of social scientists and borrowing their ideas,” says Nicholas Christakis, a physician and medical sociologist and coauthor of Connected: The Surprising Power of Our Social Networks and How They Shape Our Lives (2009).