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In this video, Wander reflects on how social computation helps in our understanding of the different social phenomena that happen in networks.
WANDER JAGER: In this module, you learned how social computation helps us to understand how various types of influences spread over social networks. Different phenomena can be studied, for example, the spreading of viruses or how norms propagate through social networks or how information is being spread. Knowing that is very good to get a better understanding of the dynamics of, for example, opinion polarisation and conflict. A better understanding helps us to support the spreading of beneficial behaviours in society, to diagnose, for example, how conflicts emerge, and perhaps more importantly, what strategies would work in resolving social conflict. But of course, networks are everywhere in nature. We have to realise that we are deeply connected with nature.
Some people even consider the whole world as a one connected organism, Gaia. It is important for us to understand how we, as humans, take stuff from natural systems but also what we offer.

In this concluding video, Wander explains the value of social computation in understanding network dynamics. Processes such as opinion dynamics, polarisation and innovation diffusion can be better understood by experimenting with the dynamics using computational simulations. This may help in the identification of strategies to mitigate problems, such as societal conflict, or the spreading of environmentally benign behaviours. Wander concludes with remarks on the deeply networked nature of life on Earth.

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Social Network Analysis: The Networks Connecting People

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