I am still reading at 10:13 PM, but wanted to take a break to post. Duncan Watts sure does get around. His circle of friends (or shall I call them a network of brainiacs) seem endless. He is well connected on the research front. I feel like I have been bouncing across the pages like the old video game ...Pong. He bounces back and forth from Steve to Mark to Peter to Chuck to Mark (again) and Jon . He collaborates with his cohorts to explore questions of networks, how they form, how they grow, how they spread or what makes them die.
"what are the patterns of interactions between individuals in a large system that we should pay attention to?" (page 27) He approaches his topic from different angles, studying from the viewpoint of the cricket, the macro to micro, individuals to mobs, physical to virtual. Watts is trying to understand the dynamics of networks, communication and systems.
He uses available free data, to study trends, statistics and different distribution patterns, trying to understand networks. One such interesting piece of data analysis produced the Kevin Bacon – Distribution of Actors According to Bacon Number -- amazing! Watts studies message chains and relation links trying to understand characteristics and behaviors. “…almost everyone in the giant component can be reached in 4 steps or less.”( page 94)
Watts talks about problems beyond the small world network with scale and cutoff regions (page 112), “the real constraint is with people themselves, who only have enough time, energy, and interest to befriend so many others before the shear effort of it all overwhelms them.”
He seems to float around the academia circuit like a virus, connecting, stimulating and infecting others with his ideas and theories on networks systems. I will say that he does attack an issue and not let go. He draws others in from his net of relationships to gain insight to his theories. He looks at the components, cave, and clusters of small networks. He is himself, a research specimen of his network investigation.
Watts uses mathematics, science, biology, psychology, sociology and physics to name a few approaches to attack his theories. He even notes that it is dangerous to assume from previous research such as the findings of Milgram. (page 132) I thought this insight was key, as research can be skewed by the researcher’s biases and pre-conceived notions about conclusions.
So how does this relate to my world? I am working with a team of people about to implement an electronic clinical research management system. This system will give researchers electronic access to other studies and the data that results on a broad scale much like the scientific publishing repository for prepublication research papers of sub disciplines of physics called the LANL (page 123). Eventually, there will be a repository of (de-identified) data that can be shares and mined for research purposes to reach conclusions using networks to study systems much like these in this book. Collaboration will hopefully open the door to treatment and scientific development that could lead to curing diseases.
He sums it up on page 15,"...one thing I hope to convey in this book is a sense of where the science of networks comes from, how it fits into the larger scheme of scientific progress, and what it can tell us about the world itself."
I am hopeful that scientific collaboration through multidisciplinary networks can lead to exciting new discoveries and cures.