Many social and economic systems are complex, in the sense that an emergent behavior arises as a product of the interaction of their constituents, such as: Waves of activity in social media, public opinion formation, product adoption, social norms, language propagation, culture, urban segregation, social networks, etc. Interestingly, simple models focused on microscopic dynamics (i.e. at the level of individuals) can unveil the mechanisms that trigger those macroscopic behaviors. Paradigmatic models usually have very few parameters that - when changed - give rise to changing macroscopic behavior. The most didactic way to explore this rich phenomenology is to interactively modify said parameters and observe the changes in global behavior and in the natural evolution of it. When teaching (and in absence of the framework proposed here) two choices are possible: Either the lecturer verbosely explains the global properties of the system or the students must program the algorithms implementing them. Given the multitude of phenomena that are introduced in a course, the second choice is unfeasible, while the first option is not the most efficient way of communicating the richness of the systems under study. This project intends to develop a software framework that allows lecturer and students to visualize and interact with fundamental models of social and economic systems. Most importantly,
this framework makes use of standardized, state-of-the-art web technologies that enable such interaction in a variety of devices without the need of installing any piece of software. This way, we achieve broad accessibility of the learning materials, visual memory, and intuition on the dynamics and properties observed in the subjects of study. The interest of this framework is not limited to classes in the field of Network and Data Science of the WWF, but can also become a fundamental tool for research activities of the URPP Social Networks and the entire DSI.
Goal of the project
The objective of this proposal is the development of a high-performance software framework that allows students to interact with paradigmatic models that highlight the mechanisms behind emergent global properties of socio-economic systems and social and economic network evolution. Additionally, it aims to provide the ability to display the evolution of systems composed of hundreds or even thousands of agents in a responsive manner: a student (or lecturer) changing a parameter would immediately be reflected in the observed dynamics. The framework should allow the programs to be run in modern web browsers, without the need of installation of any specialized software. As a result, students would be able to gain intuition and experience in the largely nontrivial effects that some of the model parameters play in the overall system properties. The immediate target groups of this proposal are students of Master courses related to Network Science that involve modelling and analysis of complex socio-economic systems (Network Theory and Analytics and Agent-Based Modelling and the course to be offered since 2018 on Networks in Business), social networks, the mechanisms behind network growth, etc. In the long run, this platform would allow to cement activities in such a way that students can extend the platform by programming in computer languages that are more familiar to
them. Lastly, outreach activities of the URPP Social Networks and of the DSI will largely benefit from this platform because of the reusability with which it will be designed.
Advancement of teaching
In this framework, students can interact with some of the models presented in the lectures without having to program all the contents of the course themselves. While we maintain that the programming exercises are a core competence for a deep understanding of the phenomenologies presented, the palette of content in the courses and the specific nature of the skills required to program high quality
visualizations make it unfeasible to add this as an objective for the courses. Therefore, a unified framework with implementations of the models presented in the lecture will allow the students to gain more insight in the way the models work, far beyond the passive learning in class. It will also improve the lectures by making the explanations more appealing and rich in content. The didactic possibilities of this approach are vast, and have not been developed so far at the UZH. Further, the deliverables can be used in research activities of the URPP Social Networks for seminars and outreach webpages when revealing our research output. Some of the models involve computer programming, however, having interactive applets that allow modifying setups and observing the changes is a great benefit for the teaching process and for students to get in touch with the subjects of their study.