How the New Science of Computational History Is Changing the Study of the Past

From the MIT Technology Review:

One of the curious features of network science is that the same networks underlie entirely different phenomena. As a result, these phenomena have deep similarities that are far from obvious at first glance. Good examples include the spread of disease, the size of forest fires, and even the distribution of earthquake magnitude, which all follow a similar pattern. This is a direct result of their sharing the same network structure.

So it’s usually no surprise that the same “laws” emerge when physicists find the same networks underlying other phenomena. Exactly this has happened repeatedly in the social sciences. Network science now allows social scientists to model societies, to study the way ideas, gossip, fashions, and so on flow through society—and even to study how this influences opinion.

To do this they’ve used the tools developed to study other disciplines. That’s why the new field of computational social science has become so powerful so quickly.

But there’s another field of endeavor that also stands to benefit: the study of history. Throughout history, humans have formed networks that have played a profound role in the way events have unfolded. Historians have recently begun to reconstruct these networks using historical sources such as correspondence and contemporary records.

More here.