This course introduces students to the theories, concepts, and measures of Social Network Analysis (SNA), which is aimed at characterizing the structure of large-scale Online...

Nowadays, due to the SARS-CoV-2 pandemic, epidemic modeling is experiencing a constantly growing interest from researchers of heterogeneous fields of study. Indeed, the vast...

Online information intermediaries such as Facebook and Google are slowly replacing traditional media channels thereby partly becoming the gatekeepers of our society. To deal...

Algorithms are now regularly used to decide whether defendants awaiting trial are too dangerous to be released back into the community. In some cases, black defendants are...

This course, initially designed for social scientists, covers several topics of data science. Python programming Data Cleaning and Transformation Classification Clustering...

Building on studies of the collective dimension of data protection, this article sets out to embed this new perspective in an assessment model centred on human rights (Human...

This paper presents a framework for research infrastructures enabling ethically sensitive and legally compliant data science in Europe. Our goal is to describe how to design...

The word ‘pattern’ frequently appears in the visualisation and visual analytics literature, but what do we mean when we talk about patterns? We propose a practicable...

Accountability is the ability to provide good reasons in order to explain and to justify actions, decisions, and policies for a (hypothetical) forum of persons or...

The most effective Artificial Intelligence (AI) systems exploit complex machine learning models to fulfill their tasks due to their high performance. Unfortunately, the most...

The ever-increasing application of algorithms to decision-making in a range of social contexts has prompted demands for algorithmic accountability. Accountable decision-makers...

Algorithmic systems increasingly shape information people are exposed to as well as influence decisions about employment, finances, and other opportunities. In some cases,...

Traditional statistical data on international migration suffers from the problems (gaps) of inconsistency in definitions, differences in geographical coverages, absence of...

In recent years, many accurate decision support systems have been constructed as black boxes, that is as systems that hide their internal logic to the user. This lack of...

Community discovery is one of the most challenging tasks in social network analysis. During the last decades, several algorithms have been proposed with the aim of identifying...

This set of tutorials provides an introduction to Social Network Analysis in Python with networkx. Topics covered: Introduction to NetworkX NDlib: Network Diffusion library...

Social Network Analysis course @ Master SoBigData This course introduces students to the theories, concepts and measures of Social Network Analysis (SNA), that is aimed at...