People, Networks and Neighbours: Understanding Social Dynamics
Learn why social processes seem so unpredictable and understand better the basics of social dynamics with experts from the University of Groningen.
Duration
3 weeks
Weekly study
4 hours
100% online
How it works
Unlimited subscription
Learn more
This three-week course will help you understand why social processes seem so unpredictable and understand better the basics of social dynamics. It’s designed to show you a new interesting way of approaching questions about social behaviour. Throughout, you’ll focus on social mechanisms and will explore how models and simulations can help to understand those mechanisms.
You’ll gain an understanding of how the behaviour of individuals can lead to unexpected results on a group or societal level. You’ll also explore a new way of looking at social phenomena by focussing on underlying mechanisms, and will investigate how models can help decipher social processes.
You’ll also explore how similar social processes occur across different contexts, and will experiment with a simple pen-and-paper model and a computer simulation of a social mechanism. Finally, you’ll identify the opportunities that computational social sciences (CSS), especially modelling and simulations, offer for understanding social processes.
Throughout the course you will be investigating some simple social processes with the help of models that illustrate how humans behave and how they influence each other. For that we will use examples, animations and game-like tools - no mathematical and programming skills are required!
In this activity, you will consider why social processes seem so unpredictable and have a closer look at one specific process of organising a protest.
In this activity, you will investigate a very simple model of how a protest comes to life and explore how micro behaviours lead to unexpected outcomes on a social level.
In this activity, you will explore how a small change can have a big impact on the final outcome and how it is important to think about mechanisms leading from individual behaviours to the results on a societal level.
In this activity, you will learn what model, modelling and simulations are - on the basis of your experiences with the protest organisation example.
We wrap up the week.
In this activity we will discuss why we sometimes imitate other people’s behaviour.
In this activity, we will investigate how a protest may spread via friendship relations. We will also start looking at the way networks of relations influence our decisions.
In this activity, we will discuss what Social Network Analysis is and explore the world of networks around us.
In this activity we will focus on measuring social dynamics, we will investigate the ways that the numbers grow and find out what a nonlinear process is.
In this activity, we will discuss why we need computational models to study complex processes and what is the added value of simulating social processes.
In this activity, you will consider how sometimes protest comes in a ‘spatial’ form and consider how some processes may spread via neighbour-to-neighbour influence.
In this activity, you will investigate a model of a process that spreads in space and we will focus on the process of creating this model, both by looking at individuals and their surroundings.
In this activity, you will explore the model further, this time on a bigger scale and you will see the results of the process from a bird’s eye view.
In this activity, you will experiment with different cities with the help of a simple simulation tool (no need to install anything!) and you will observe how protests spread depending on different initial conditions.
In this activity, you will first investigate how both the number of initiators and the average threshold level impact the final patterns and afterwards we will sum up the results of all experiments.
In this activity, you will learn about agent-based models (ABMs) - on the basis of spatial protest simulations - and explore some real-life applications of those models.
You have reached the end of this course. Thanks for participating! In this activity, we will quickly wrap up the contents of the whole course and point to some directions on how you can study computational models further.
More courses you might like
Learners who joined this course have also enjoyed these courses.
©2025 onlincourse.com. All rights reserved