Network Theory and Big Data
This article describes the various motivations and history behind the increasing importance of network theory. From early Londoners mapping the London Tube to find convenient routes to the “six degrees of separation” of Kevin Bacon (which describes how everyone is at most six “hops” away from Kevin Bacon, a prolific actor). However, unlike other sciences, the article argues that describing such networks at a fundamental level becomes harder and harder due to them becoming more complex as the structures they describe become larger and larger. For example, though physicists can produce theories and laws about subatomic particles and biologists can experiment on cells and molecules, mapping out an entire society would be a different task altogether. With the explosion in population and the invention of the Internet, these networks can only become more complex. As such, the mathematics that we use to develop models for such networks are becoming increasingly irrelevant. At this point, the article argues that Big Data offers a solution to such complex networks. In fact, physicist Albert-László Barabási of Northeastern has claimed to have found the existence of “hubs” that controlled the behavior of thousands of other nodes. Furthermore, these hubs not only apply to websites, but also to networks of microscopic scale such as molecules as well.
Equipped with this new knowledge of the ubiquitous nature of networks and the underlying mathematic laws, researchers had been able to tackle issues such as the H1N1 virus (swine flu) and cell phone networks during disasters such as the Boston Marathon bombing. Additionally, in the case of the swine flu network, the article explains that one of the initial proposed solutions to blocking the rapid spread was to halting entire airports. However, utilizing network theory, this “solution” would only delay the epidemic for several weeks. Similar to the Kevin Bacon’s “six degrees of separation,” the interconnectedness of society would actually prove to be the downfall of it as well. The argument against this solution was not made by doctors, though. In fact, it was physicists who utilized the same ideas of networks to prove it.
Source:
https://www.npr.org/sections/13.7/2017/11/17/564671867/the-big-idea-behind-big-data