The last decade has seen an explosion in interest in networks. Some fields – such as sociology – have been grappling with network phenomenon for decades. Others, like mathematics, have been grappling with network attributes for centuries. But, starting in the late 1990′s, networks moved from being the exclusive domain of researchers to being a common phenomenon that we all experience on a daily basis. Why? I’ve previously addressed this in a brief history of networked learning (.rtf) – essentially, we experience network effects through the internet, mobiles, and social media. With Facebook, LinkedIn and other social network services, for example, we directly experience networks in how we connect to others, share information, and get answers to questions. Instead of an abstract theoretical concept, we understand networks in the small details of our lives.
Harvard has published a nice introduction to networks: “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.”
The last sentence is key in understanding where the use of networks in society is trending: the general understanding of network properties sets in place the ability to analyze, predict, customize, etc. what individuals experience. Networks are no longer a means of understanding the present or the past, but a means by which to understand (probabilistically) the future behaviours of individuals, markets, and cells, as well as the flow of ideologies and information. Analytics are the next logical point of interest in networks.