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Seeing without knowing. Limitations of transparency and its application to al...
Models for understanding and holding systems accountable have long rested upon ideals and logics of transparency. Being able to see a system is sometimes equated with being able... -
Geo-semantic-parsing AI-powered geoparsing by traversing semantic knowledge g...
Online social networks convey rich information about geospatial facets of reality. However in most cases, geographic information is not explicit and structured, thus... -
Towards better social crisis data with HERMES Hybrid sensing for EmeRgency Ma...
People involved in mass emergencies increasingly publish information-rich contents in Online Social Networks (OSNs), thus acting as a distributed and resilient network of... -
Interaction Strength Analysis to Model Retweet Cascade Graphs
Tracking information diffusion is a non-trivial task and it has been widely studied across different domains and platforms. The advent of social media has led to even more... -
Social Network Analysis @MasterBigData2022
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...-
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Private Deliverable D2.3 Report on WP2 activities
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UTLDR: an agent-based framework for modelling infectious diseases and public ...
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...-
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Bias in algorithmic filtering and personalization
Online information intermediaries such as Facebook and Google are slowly replacing traditional media channels thereby partly becoming the gatekeepers of our society. To deal... -
Algorithmic decision making and the cost of fairness
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... -
Introduction to Data science for Social Scientists
This course, initially designed for social scientists, covers several topics of data science. Python programming Data Cleaning and Transformation Classification Clustering...-
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AI and Big Data A blueprint for a human rights and social and ethical impact ...
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... -
An ethico-legal framework for social data science
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... -
Accountability for the Use of Algorithms in a Big Data Environment
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... -
Algorithmic Accountability and Public Reason
The ever-increasing application of algorithms to decision-making in a range of social contexts has prompted demands for algorithmic accountability. Accountable decision-makers... -
A qualitative exploration of perceptions of algorithmic fairness
Algorithmic systems increasingly shape information people are exposed to as well as influence decisions about employment, finances, and other opportunities. In some cases,... -
Can Big Data Bridge Gaps in Migration Statistics
Traditional statistical data on international migration suffers from the problems (gaps) of inconsistency in definitions, differences in geographical coverages, absence of...-
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Social Network Analysis with Python
This set of tutorials provides an introduction to Social Network Analysis in Python with networkx. Topics covered: Introduction to NetworkX NDlib: Network Diffusion library...-
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Social Network Analysis
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...-
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A Learned Approach to Quicken and Compress Rank Select Dictionaries
We introduce the first “learned” scheme for implementing a compressed rank/select dictionary. We prove theoretical bounds on its time and space performance both in the worst...
