Complexity_ A Guided Tour - Melanie Mitchell [119]
Epidemiologists studying sexually transmitted diseases often look at networks of sexual contacts, in which nodes are people and links represent sexual partnerships between two people. Recently, a group consisting of sociologists and physicists analyzed data from a Swedish survey of sexual behavior and found that the resulting network has a scale-free structure; similar results have been found in studies of other sexual networks.
In this case, the vulnerability of such networks to the removal of hubs can work in our favor. It has been suggested that safe-sex campaigns, vaccinations, and other kinds of interventions should mainly be targeted at such hubs.
How can these hubs be identified without having to map out huge networks of people, for which data on sexual partners may not be available?
A clever yet simple method was proposed by another group of network scientists: choose a set of random people from the at-risk population and ask each to name a partner. Then vaccinate that partner. People with many partners will be more likely to be named, and thus vaccinated, under this scheme.
This strategy, of course, can be exported to other situations in which “hub-targeting” is desired, such as fighting computer viruses transmitted by e-mail: in this case, one should target anti-virus methods to the computers of people with large address books, rather than depending on all computer users to perform virus detection.
FIGURE 16.1. Example of a food web. (Illustration from USGS Alaska Science Center, [http://www.absc.usgs.gov/research/seabird_foragefish/marinehabitat/home.html].)
Ecologies and Food Webs
In the science of ecology, the common notion of food chain has been extended to food web, a network in which a node represents a species or group of species; if species B is part of the diet of species A, then there is a link from node A to node B. Figure 16.1 shows a simple example of a food web.
Mapping the food webs of various ecosystems has been an important part of ecological science for some time. Recently, researchers have been applying network science to the analysis of these webs in order to understand biodiversity and the implications of different types of disruptions to that biodiversity in ecosystems.
Several ecologists have claimed that (at least some) food webs possess the small-world property, and that some of these have scale-free degree distributions, which evolved presumably to give food webs resilience to the random deletion of species. Others ecologists have disagreed that food webs have scale-free structure, and the ecology research community has recently seen a lot of debate on this issue, mainly due to the difficulty of interpreting real-world data.
Significance of Network Thinking
The examples above are only a small sampling of the ways in which network thinking is affecting various areas of science and technology. Scale-free degree distributions, clustering, and the existence of hubs are the common themes; these features give rise to networks with small-world communication capabilities and resilience to deletion of random nodes. Each of these properties is significant for understanding complex systems, both in science and in technology.
In science, network thinking is providing a novel language for expressing commonalities across complex systems in nature, thus allowing insights from one area to influence other, disparate areas. In a self-referential way, network science itself plays the role of a hub—the common connection among otherwise far-flung scientific disciplines.
In technology, network thinking is providing novel ways to think about difficult problems such as how to do efficient search on the Web, how to control epidemics, how to manage large organizations, how to preserve ecosystems, how to target diseases that affect complex networks