Exchange of information

WANDER JAGER: In the previous exercise, we saw that herpes play a critical role in speed and degree of the spreading of the virus. Due to their larger number of links, herpes have a larger chance of picking up the virus and then spread it to all their links. In terms of a virus, we don’t speak of a super spreader. A celebrity by shaking many hands may be more susceptible for picking up a virus and then infecting many others. However, not all influences travel through a network like a virus does. A celebrity will most certainly not read all the responses to his or her tweets, Facebook posts, or pictures shared on Instagram. Hence, information travels differently than a virus on the network.

Because people have a limited capacity for knowing and following other people, a popular person, like a celebrity or politician, will only be informed by a small number of other people. A celebrity may have millions of followers on social media but obviously, will not follow everyone back. When there is a difference between the number of in going influences and number of outgoing influences, we speak of a directed network. Outgoing influences can be numerous due to the press, television, and social media. In going influences on the contrary are limited by our social cognitive capacity. Think of the Dunbar number mentioned before, indicating that our social cognition is limited to a tribe of about 150 people.

The social scientists have studied a lot, what kind of influences take place in these kinds of direct networks. What kind of factors are of influence of people connecting with one another. One of the things that we found is very important is the similarity between people. You can see that in real life but also on for example, Twitter, people with the same opinions seem to cluster. Another element that seems to be very important than networks are norms. When do you follow the behaviour of other similar people. And when do you dare to deviate from the norm. Social computation helps us to unravel how certain societal phenomena emerge from specific interactions between networked individuals.

Social computation offers a perfect control over network structure and allows for implementing theoretical ideas on how disconnected agents interact. In this way, social computation allows for exploring how social phenomena emerge. We called nodes that represent humans agents because they can be equipped with an agency to respond to information and actions of other agents. For example, referring to the preference to interact with others similar to them, we can implement that agents prefer to do what their linked others are Alters do. Following the behaviour of the local majority operates, like conforming to the norm. A widely studied phenomenon and human behaviour. In the next exercise, you can explore for yourself how norms operate in a social network.