Publications associées à Personalized News Recommendation with Context Trees

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

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

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

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

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

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

A dashboard for controlling polarization in personalization

Nisheeth Vishnoi, Farnood Salehi, Laura Elisa Celis, Vijay Keswani, Sayash Kapoor

Personalization is pervasive in the online space as it leads to higher efficiency for the user and higher revenue for the platform by individualizing the most relevant content for each user. However, recent studies suggest that such personalization can lea ...

IOS PRESS2019

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

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

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

Frédéric Kaplan, Giovanni Colavizza

Early modern printed gazettes relied on a system of news exchange and text reuse largely based on handwritten sources. The reconstruction of this information exchange system is possible by detecting reused texts. We present a method to individuate text bor ...

Springer International Publishing2015

Aggregating information from the crowd : ratings, recommendations and predictions

Florent Frédéric Garcin

With an ever-growing amount of data generated on the web, aggregating information from the crowd into meaningful knowledge has become crucial to companies in order to create a competitive edge. Not only companies, but also organizations and governments can ...

EPFL2014

PEN recsys: a Personalized News Recommender Systems Framework

Boi Faltings, Florent Frédéric Garcin

We present the Personalized News (PEN) recommender systems framework, currently in use by a newspaper website to evaluate various algorithms for news recommendations. We briefly describe its system architecture and related components. We show how a researc ...

2013

PEN recsys: a Personalized News Recommender Systems Framework (DEMO)

Boi Faltings, Florent Frédéric Garcin

We present the Personalized News (PEN) recommender systems framework, (Note that this paper is an extended abstract of Garcin2013b), currently in use by a newspaper website to evaluate various algorithms for news recommendations. We briefly describe its sy ...

2013

CoFeed: privacy-preserving Web search recommendation based on collaborative aggregation of interest feedback

Pascal Felber, Martin Rajman, Vinh Toan Luu

Search engines essentially rely on the structure of the graph of hyperlinks. Although accurate for the main trend, this is not effective when some query is ambiguous. Leveraging semantic information by the mean of interest matching allows proposing complem ...

Wiley-Blackwell2013

WHATSUP: A Decentralized Instant News Recommender

Rachid Guerraoui, Anne-Marie Kermarrec, Davide Frey

We present WhatsUp, a collaborative filtering system for disseminating news items in a large-scale dynamic setting with no central authority. WhatsUp constructs an implicit social network based on user profiles that express the opinions of users about the ...

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

A Social Media Platform in Higher Education

Denis Gillet, Christophe Salzmann, Sandy Ingram, Evgeny Bogdanov, Na Li

This paper reports on the successful use of Graasp, a social media platform, by university students for their collaborative work. Graasp features a number of innovations, such as administrator-free creation of collaborative spaces, context-aware recommenda ...

2012