Publications associées à Mapping the Early Modern News Flow: An Enquiry by Robust Text Reuse Detection

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

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, Panagiotis Smeros, Angeliki Romanou

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

SciLens News Platform: A System for Real-Time Evaluation of News Articles

Karl Aberer, Panagiotis Smeros, Angeliki Romanou, Carlos Castillo

We demonstrate the SciLens News Platform, a novel system for evaluating the quality of news articles. The SciLens News Platform automatically collects contextual information about news articles in real-time and provides quality indicators about their valid ...

ASSOC COMPUTING MACHINERY2020

The Fake News Vaccine

Rachid Guerraoui, Willy Zwaenepoel, Anne-Marie Kermarrec, Oana Maria Balmau, Matej Pavlovic, Alexandre David Olivier Maurer

While spreading fake news is an old phenomenon, today social media enables misinformation to instantaneously reach millions of people. Content-based approaches to detect fake news, typically based on automatic text checking, are limited. It is indeed diffi ...

2019

SciLens: Evaluating the Quality of Scientific News Articles Using Social Media and Scientific Literature Indicators

Karl Aberer, Panagiotis Smeros, Carlos Castillo

This paper describes, develops, and validates SciLens, a method to evaluate the quality of scientific news articles. The starting point for our work are structured methodologies that define a series of quality aspects for manually evaluating news. Based on ...

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

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

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

Probing the Limits of Social Data : Biases, Methods, and Domain Knowledge

Alexandra Olteanu

Online social data has been hailed to provide unprecedented insights into human phenomena due to its ability to capture human behavior at a scale and level of detail, both in breadth and depth, that is hard to achieve through conventional data collection t ...

EPFL2016

Comparing Events Coverage in Online News and Social Media: The Case of Climate Change

Karl Aberer, Alexandra Olteanu, Carlos Castillo

Social media is becoming more and more integrated in the distribution and consumption of news. How is news in social media different from mainstream news? % This paper presents a comparative analysis covering a span of 17 months and hundreds of news events ...

2015

Personalized News Recommendation with Context Trees

Boi Faltings, Florent Frédéric Garcin, Christos Dimitrakakis

The proliferation of online news creates a need for filtering interesting articles. Compared to other products, however, recommending news has specific challenges: news preferences are subject to trends, users do not want to see multiple articles with simi ...

2013

Personalized news recommendation based on collaborative filtering

Boi Faltings, Vincent Jean Fabrice Schickel, Florent Frédéric Garcin

Because of the abundance of news on the web, news recommendation is an important problem. We compare three approaches for personalized news recommendation: collaborative filtering at the level of news items, content-based system recommending items with sim ...

2012