Let's start with the first lecture. You can find it here.
In this post I summarise (certainly in a very personal fashion, although some points are directly extracted from his slides) the learning points I extracted from the lecture.
- We find networks in many different fields.
- They can be used to explain very different things happening in real life.
- A network is a collection of edges and nodes or vertices (plural of vertex). These words are taken from Spatial Mathematics.
- Although the border among them is blurred. He proposes 4 types of networks: Technological, information, biological and social networks.
Technological networks
- One example, the Internet is a complex network. Even though we human beings built it, we do not know its structure. However, we can make a scientific experiment and try to identify its structure. For example, using the program traceroute.
- When we see the result, we start understanding why the study of complex networks (e.g. with billions of nodes) help us making networks e.g. more efficient and more robust.
- Some human-made networks are the Internet and the air transportation network. These are technological networks.
- In some networks we are interested in their static structure. In some others, for example in the airline network, we are also interested in the dynamics of the nodes, cities connected by flights and edges, the flights themselves. The dynamic study of a complex network is actually the cutting edge of network science these days.
Information networks
- Regarding information networks, for example the World Wide Web, where the nodes are web pages and the edges are the hyperlinks you can find in the web pages.
- A hyperlink has its direction. So, the WWW is a directed network. In 1990 there were around 20 pages. In 2010 Google listed more than 25 billion. Actually the number of pages is now infinite. Some pages didn't exist until you asked for.
- A recommendation network (e.g. books in Amazon that could be of your interest) is also an information network.
Biological networks
- An example is the metabolic network or the neural network.
- A food web (which species eats which species) is also an example of a complex network.
- A self-edge in the food web represents canibalism.
Social networks
- His favorite. Jacob Moreno in 1934 already talked about sociograms. He observed kids playing in the playground.
- Actually, even Newman's grandfather, in a scientific paper, mentioned the idea of a social network.
Measuring social networks
- This is a complex endeavour. How can we measure? By observation, interviews, questionnaires, online data, archival records and message passing.
- Social networks govern the way diseases spread.
- Political connections, business board connections, dating connections are only some examples of complex networks.
The understanding of complex networks is still basic.
In the second lecture, once he has explained how networks are described, Mark Newman will talk about how can these network diagrams be used.
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| Foggy networks? |
