Nodes and links

WANER JAGER: Just like all living creatures, we are a network species, and we constantly communicate. We can exchange useful information, gossip, and infectious diseases. And all these interactions take place in a globally connected world. Some exchanges require a person-to-person interaction, such as the transmission of a virus. Keeping sufficient distance from each other makes it difficult for a virus to jump from one person to another. Here, we see that people in the city park of Groningen, The Netherlands, cluster and small natural groups, keeping distance to avoid COVID-19 from spreading. Network theory explains this– how information travels from one person to another. In network theoretical terms, we are talking about how information from one node may travel to another node.

The connections between these nodes are called links. The concepts of links and nodes are essential to network theory. Computational methods allow for building networks of connecting agents, and thus, for conducting experiments on how different influences travel through networks. These influences can range from sharing bacteria and viruses, information on products, cultural norms, and many more. Human networks can be extremely complex. And the links connecting us can exist in physical space, but also on the internet. And we can even connect with people from the past, because we store a lot of information. To model these networks in computational social science, we have to start simply.

Early social computational models were based on having a roster of cells, as drawn here in the sand. And the state of one cell would affect the state of another cell. For example, if this middle cell gets infected, for example, with a disease, it could spread out the disease to the next adjacent cells. So the neighbours are being infected.

Models based on a physical grid, where cells influence each other are called cellular automata. One of the most famous examples of this is the Game of Life as invented by the late mathematician James Conway. When only the four adjacent cells are affected, network scientists call this a Von Neumann neighbourhood. If the four diagonal cells are also affected, we speak of a Moore neighbourhood. However, much of our interactions are not confined to this physical space. People don’t live in a checkerboard world. We can travel, write emails, post on Twitter, and sometimes, a single person, like a politician or an artist, can communicate to millions of other people.

To capture that, we have to go beyond physical space restrictions in our social computational modelling of networks.