Publications associées à Journal télévisé

It’s All Relative: Learning Interpretable Models for Scoring Subjective Bias in Documents from Pairwise Comparisons

Matthias Grossglauser, Aswin Suresh, Chi Hsuan Wu

We propose an interpretable model to score the subjective bias present in documents, based only on their textual content. Our model is trained on pairs of revisions of the same Wikipedia article, where one version is more biased than the other. Although pr ...

2024

Quote Erat Demonstrandum: AWeb Interface for Exploring the Quotebank Corpus

Robert West, Akhil Arora, Andreas Oliver Spitz, Huan-Cheng Chang, Vuk Vukovic

The use of attributed quotes is the most direct and least filtered pathway of information propagation in news. Consequently, quotes play a central role in the conception, reception, and analysis of news stories. Since quotes provide a more direct window in ...

ASSOC COMPUTING MACHINERY2022

How Did Europe's Press Cover Covid-19 Vaccination News? A Five-Country Analysis

Daniel Gatica-Perez

Understanding how high-quality newspapers present and discuss major news plays a role towards tackling disinformation, as it contributes to the characterization of the full ecosystem in which information circulates. In this paper, we present an analysis of ...

Assoc Computing Machinery2022

Combating Online Scientific Misinformation

Panagiotis Smeros

The drastic shift towards digital communication in our mediasphere has caused a profound change in the production and consumption of information, which in turn has substantial implications on the social and political landscape. Misinformation, as a side ef ...

EPFL2022

On Representation Learning for Scientific News Articles Using Heterogeneous Knowledge Graphs

Karl Aberer, Angeliki Romanou, Panagiotis Smeros

In the era of misinformation and information inflation, the credibility assessment of the produced news is of the essence. However, fact-checking can be challenging considering the limited references presented in the news. This challenge can be transcended ...

ASSOC COMPUTING MACHINERY2021

Reports of the Workshops Held at the 2020 International Association for the Advancement of Artificial Intelligence Conference on Web and Social Media

Panagiotis Smeros, Jérémie Rappaz

The workshop program of the Association for the Advancement of Artificial Intelligence's Fourteenth International Conference on Web and Social Media was held June 8 to 20, 2020. The conference venue, which had originally been Atlanta, Georgia, USA, had to ...

AMER ASSOC ARTIFICIAL INTELL2020

A Dynamic Embedding Model of the Media Landscape

Karl Aberer, Jérémie Rappaz

Information about world events is disseminated through a wide variety of news channels, each with specific considerations in the choice of their reporting. Although the multiplicity of these outlets should ensure a variety of viewpoints, recent reports sug ...

ASSOC COMPUTING MACHINERY2019

Debunking Misinformation on the Web: Detection, Validation, and Visualisation

Thành Tâm Nguyên

Our modern society is struggling with an unprecedented amount of online misinformation, which does harm to democracy, economics, and cybersecurity. Journalism and politics have been impacted by misinformation on a global scale, with weakened public trust i ...

EPFL2019

Automatic Online Fake News Detection Combining Content and Social Signals

Stefano Moret, Gabriele Ballarin

The proliferation and rapid diffusion of fake news on the Internet highlight the need of automatic hoax detection systems. In the context of social networks, machine learning (ML) methods can be used for this purpose. Fake news detection strategies are tra ...

IEEE2018

Selection Bias in News Coverage: Learning it, Fighting it

Karl Aberer, Jérémie Rappaz

News entities must 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, res ...

2018