Network science, the new ABCs of life

A new way of looking at the world is emerging by studying the patterns in everyday life

Every schoolboy must have been taught this story: It is the middle of the 17th century, a wave of bubonic plague is sweeping through England, closing all schools and colleges. Twenty-three-year-old Isaac Newton is forced to leave Cambridge University, where he is a researcher, and go back to his home town in Lincolnshire and seek refuge in the small house where he was born and grew up. There, one evening, the weather being warm, he went down to the garden and sat down to enjoy a cup of tea in the shade of an apple tree when an apple landed plunk on his head. What made the apple fall straight down, he wondered and not sideways or upward? It must be because the Earth’s matter draws it? Is there a drawing power in the Earth’s matter? In all matter? What is this power that draws one object to the other? This line of thinking led Newton to his theory of gravity, and from there to the foundation of the science of physics. This is how science progresses: Observing a pattern in everyday life and constructing a theory about it, which then explains a much wider range of similar events.
 
A similar search for patterns in mundane events is now focusing its attention on, god forbid, patterns of human behaviour. “Are our actions governed by rules and mechanisms that in their simplicity match the predictive power of Newton’s law of gravitation…might we go so far as to predict human behaviour”, asks Albert-Laszlo Barabasi in his new book Bursts, The Hidden Patterns Behind Everything We Do, From Your Email to Bloody Crusades. He recounts, in this book, some extraordinary findings. For example, he and his co-workers found in analysing email data that we as human beings have short periods of intense email activity followed by long periods, often days, of no emails. Lest we conclude that this type of “bursty” human behaviour is specific to email activity, he and his coworkers analysed that the paper mail correspondence of Albert Einstein in the 1905-1910 period also followed a similar burst pattern!
 
A big area of research currently attempts to understand how another common pattern in everyday life, social networks, among human beings operate. An example of one such pattern that is receiving a lot of attention is citation networks. These occur when the author of a scientific paper cites other scientific papers. In the academic world, the number of research papers you publish in quality journals and the number of other papers citing your papers can make all the difference in whether you get promoted or hired by prestigious universities. Researchers are now closely studying the patterns of such citations to detect patterns. One such pattern already noticed is the “citation cartel” that has been established in order to make the difference between the quality of the scientists, measured by the number of cites, higher. Network analysis is also revealing groups of editors and journals working together for mutual benefit by using the inter-journal cites to increase the impact factors of their journals as also other relationships, like editor to authors or authors to authors.
 

Illustration by Binay Sinha

A wide range of networks are being currently researched — financial networks to detect insider trading, terrorist networks to detect their emergence being two examples
 
Such deep study of networks is already yielding techniques to elevate this field almost to the same level as that of the traditional sciences such as physics and chemistry and with a similar set of abstract concepts. “Size” of a network is now defined as the sum total of the links between the actors (called “nodes”) in the network. “Density” is the ratio of the number of links (called “edges”) between actors divided by the number of all possible links. The “degree” of an actor or node is the number of links (or edges) connecting to it. The “node centrality” measure tells you how import the role of each node ( or actor) is in the network, to name some of the emerging scientific terminology in the emerging science of “network science”.
 
It turns out that even successes of artists can be traced to their position in network. For example, researchers at the Network Science Institute, Northeastern University, Boston, reconstructed the exhibition history of half a million artists, mapping out the co-exhibition network that captures the movement of art between institutions. Centrality within this network captured institutional prestige. They concluded that “early access to prestigious central institutions offered life-long access to high-prestige venues and reduced dropout rate. By contrast, starting at the network periphery resulted in a high dropout rate, limiting access to central institutions”.
 
Universities and governments throughout the world are rushing to set up “Network Science Centres”. The Yale Institute for Network Science is studying word-of-mouth networks to see how “buzz” happens; Harvard is pushing the study of networked medicine to research “the role, identification, and behaviour of networks in biology and disease and the integration of multiple types of data into perturbed, dynamic networks as a paradigm”. In India, green shoots can be seen at, among other places, Indian Institute of Science Education and Research at Pune, and at the Complex Systems Lab, IIT Indore.
 

The writer is the author of The Wave Rider, a Chronicle of the Information Age; ajitb@rediffmail.com