Network effects are pervasive in our society and affect many aspects of our life from how we acquire information, how we interact, how we make decisions, and what opportunities we are exposed to. This is even more the case since the rise of the Internet and online social media, which do not only provide a vast number of empirical data for the quantitative study of social systems, but have also deeply changed the pattern of how people interact with each other. In this era of information revolution and dense interactions, our society faces various unprecedented challenges with profound impacts on modern politics and economy, such as opinion polarization, the politicization of public debates, the effects of echo chambers, and filter bubbles. Phenomena such as spreading of contagion (may this be of pathogen or misinformation), coordination of strategic behavior as well as targeted interventions and incentive for efficient use of resources over networks are rapidly becoming of fundamental importance for both the society and its economy. Mathematical modeling plays a fundamental role in understanding how these macroscopic phenomena emerge from certain microscopic mechanisms of social interactions and certain network structures.

​

Exploiting the progress in complex networks and data mining, the last decades have witnessed a rapid development of the research on the statistical and static features of social networks, in the framework of Social Network Analysis. However, dynamical processes on/of social networks, which are directly related to the aforementioned phenomena, remain to be thoroughly studied. Due to the rapid progress in the study of multi-agent systems, researchers on control theory have recently contributed various useful mathematical tools to the study and control of social network dynamics. These mathematical tools make it possible for us to investigate some fundamental or emerging problems in social science, including:

(1) What is the "main factor" that governs opinion dynamics and what mechanisms could drive public opinions to polarization?

(2) How do social media and online recommendation system shape the public opinion formation processes?

(3) Is there any efficient way to mitigate the spreading of misinformation or the impact of malicious opinion manipulation?

(4) How does network structure influence individuals' strategic behavior on social networks?

(5) How can one plan targeted interventions or incentives to maximize system performance by exploiting such network effects?

​

We thus believe this is the perfect timing to bring these socio-economic questions to the attention of the broad audience of control theorists. We organized the workshop by bringing together researchers that work on this rapidly expanding area using different approaches, as for example game theory, complex network analysis, and multi-agent systems so that attendees can have a broad overview of the different techniques that one can use to answer the questions above. The aim is to give a general introduction to dynamics on socio-economic systems, as well as present the latest results on various emerging topics such as social learning and opinion dynamics, network propagation models, coordination of competitive network systems, information design, and interventions under partial information.