Media Observatory - Quantifying Media Bias
Michaël Defferrard (mdeff)
Description: Dylan Bourgeois (@dtsbourg) // I study robots and their brains.
machine learning (3372) robots (1015) epfl (62) dylan bourgeois (2) dtsbourg (2)
I studied robots and their brains at EPFL in Switzerland, and defended my Masters' Thesis from Stanford. I am currently a Senior Research Scientist at Robust.AI . You can check out my CV or get in touch here .
These publications span several concurrent domains, from the application of Machine Learning in High Energy Physics (HEP) to the development of novel characterizations of media bias. This work is the product of diverse research interests and a variety of research opportunities that I have been lucky enough to pursue. The overarching goal is to provide interpretable methods, useful in their application but that also provide a broader understanding of the problem at hand.
News entities have to select and filter the coverage they broadcast through their respective channels, since the set of world events is too large to be treated exhaustively. The subjective nature of this filtering induces biases due to, among other things, resource constraints, editorial guidelines, ideological affinities, or even the fragmented nature of the information at a journalist's disposal. The magnitude and direction of this bias are, however, widely unknown. The absence of ground truth, the sheer
Media Observatory - Quantifying Media Bias
Michaël Defferrard (mdeff)