Measuring Inequalities in Complex Systems

by Profs. Fariba Karimi and Samuel Martín-Gutiérrez,

Complexity Science Hub

Josefstädter Straße 39, 1080 Vienna (Austria)

Social groups are the fundamental components of our societies. They determine how we interact with each other and shape our institutions and collectives by building a sense of belonging. This in turn creates notions of in-group and out-group that define our preferences to connect with each other. In most cases, people prefer to connect with others similar to them, a phenomenon known as homophily. Homophily facilitates smoother coordination, better communication, and enhanced trust between individuals, but on the other hand, it also reduces diversity in knowledge, creates inequalities, and fuels polarization. In this course, we will give an overview of how social groups are formed and maintained, and what are the main societal consequences of their existence. To this end, we will explore social network models, inequality metrics, methods to analyze polarization, and spreading dynamics.

The following python packages are required for some of the hands-on session that can be downloaded from the GitHub repository:

• The ‘multipolar' package: [https://github.com/samuel-mg/multipolar]

• The 'networklnequalities' package: [https://github.com/CSHVienna/NetworkInequalities]