It's A Small World After All!!!

Though the reading from Mark Taylor’s “The Moment of Complexity” was a reading from further back, we did discuss it a little Tuesday. As I mentioned in the last reading notes blog, I felt as though writing could be both grid and network but that academic writing was clearly grid-like. After our discussion, I would like to recant that statement. I do still feel that academic writing is more grid than network, but a good example in class was the reference section of a research article. A reference section is very much a network as it connects many people, and even though it is not linking many texts quickly such as the internet, it is still linking them. So I think that trying to categorize things into grid and network is much less clear-cut than I originally thought, and almost all forms of writing and expression have both grid and network components.

Last week we read two chapters of Duncan Watts’ book “Six Degrees”, and it is undoubtedly the most interesting and smooth read that we’ve had this semester. Watts gives many great real examples of his points, and by using interesting stories, makes the reading easier to understand. Though we had very little time to actually discuss the reading, I would say that the argument made by Watts is the importance of emergence, and the interconnectedness that exists.

“How does individual behavior aggregate to collective behavior?” (Watts 24). This is a question Watts poses and it is an excellent way to think about the idea of emergence. We can seldom predict how something will work solely by knowing how the individual parts work. One example is how the brain is made up of trillions of neurons, which we know their functions well, but the brain’s overall “nature cannot be explained simply in terms of aggregations of neurons” (Watts 25). Another example of this is mobs and the idea that the mob as a whole acts differently than one would expect by looking at solely the individuals. Halloween on State Street was an example brought up in class and illustrates the way a mob can act much more differently than the individuals would on their own. It is these ideas on emergence that set the groundwork for a science on networks, where relationships among various components of a system shape the way the system work.

Networks can be extremely complex or simple, and this is highlighted by the small-world problem. The small-world problem is how people can be connected to almost anyone on the globe within a short number of degrees of separation, commonly said to be 6. I do think that to make a strong statement that everyone is definitely linked within a certain number of steps is probably unrealistic, as there has to be someone out there that has almost no part in the “worldwide network”. But I think that the small-world problem highlights an interesting point about networks in general, and that is that they can become very complex, very quick. Watts uses the pure branching network to show that a person could reach 125 people within 3 degrees of separation if each person knows 5 new people. The problem is that in the real world, pure branching is not going to happen, and that most likely many of the people you know, know those same people. This is what Watts calls “clustering”. In sort of a connection to these ideas, Watts later goes into the outbreak of diseases and viruses in the world. It can be rather terrifying to think of how simple it might be for a virus to get in one person and quickly get around the world in a matter of days through our networking. Yet, again it is seen how complicated networks can be as no virus has yet to take over the entire globe in such a manner. This can be for a variety of reasons such as infection time, contagiousness, and deadliness among others. So when taking all of the factors of some disease or virus into account, one quickly realizes that a simple model may be sufficient to get a general idea about the spread of disease, but a vastly complicated one is required to perfectly describe it. In the end, I think another major point Watts is trying to get at is the complexity of the networks that do exist, and we need to invest a lot more time and energy into studying them to truly understand aspects of life that we do not now.