Having finished the second half of this book, I think my impression of it from the first half holds true throughout: while thoroughly interesting and endlessly useful, I may have come in just expecting a more formulaic or dense structure to the information.
In “Awakening Internet” Albert-Laszlo Barabasi lays out the foundation of the idea he’ll explain the nature and consequences of for the rest of the book: the scale-free network and its structure. By explaining the humble beginnings of the internet and its development as a distributed structure, Barabasi gives readers a foundational understanding of how our most important network works.
One of my favorite quotes, although from later in the book, I think beautifully explains why this structure and its characteristics are so monumental: “There is no single node whose removal could break the web. A scale-free network is a web without a spider.”
Actually, I think this quote sums up the underlying message Barabasi is trying to explain throughout. What makes the internet a strong network is its structure: the power is decentralized, no one server holds all the keys, and the ever expanding reach of the network only makes its potential more fluid and palpable. The possible growth and preferential attachment that helps perpetuate that network is fundamental to networks in general though.
Another eloquent example was the explanation of the corporate tree: for all information flowing back up to the top, or the CEO, there has to be a lot of efficient filtration and categorization, so there isn’t and information overload when all the branches reach back to that one base.
I also really appreciated the explanation of corporate boards and how people in those circles often work on more than one board. Connecting separate companies that may benefit from each other is so crucial to connecting small worlds of nodes to other small worlds of nodes, because, as other point made in chapter 11 illustrated, hubs with a lot of connections actually move much more traffic than an even distribution among nodes. So, these tree structures that center power at a base, and these select hubs, or few people with many connections, they’re the real driving force and deciding factor in many of our networks.
Some examples Barabasi used included a study of the spread of the antibiotic Tetracycline that found, basically, that a small number of nodes have a majority of the connections. Meaning, in the four Illinois cities included, a small group of the doctors surveyed were the common connection of basically all surveyed.
An easier way for me to visualize what this means is follower ratios on Twitter. It’s actually more beneficial to have social media influencers who can act as guideposts for the internet, because as Barabasi explains, from any one page on the internet only 24% of the rest of the pages can be reached directly. To me this means that you can’t really ever predict where you’ll end up on the internet because you only know the site you’re currently on, and where you might go next. If everyone actually followed everyone, the hierarchy of information would be lost. Much like the corporate tree that leads up to the CEO, it’s better to have “viral” people and posts that create a type of landing zone to decide where you go next.
All in all I found the information in this book invaluable, and I’ve already recommended it to my friend, a software engineer who already understands the technical side of the ideas but would love the explanations and possibilities opened up by them. It’s remarkable to think about the potential of a network like the internet, and as all systems have, what other networks it have the potential to perpetuate.