Publications associées à WHATSUP: A Decentralized Instant News Recommender

Combating Online Scientific Misinformation

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

The Role of Compromised Accounts in Social Media Manipulation

Tugrulcan Elmas

In recent years we have seen a marked increase in disinformation including as part of a strategy of so-called hybrid warfare. Adversaries not only directly spread misleading content but manipulate social media by employing sophisticated techniques that exp ...

EPFL2022

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

Jérémie Rappaz, Panagiotis Smeros

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

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

Rule of Thumb – Effect of Social Button Icons on Interaction

Denis Gillet, Samuel Bendahan, Andrii Vozniuk, Adrian Christian Holzer

Social buttons are now widespread in social media apps. They are used to assign weight to user content and trigger user engagement. They come in different shapes (e.g., thumb in Facebook, arrows in Reddit or StackOverflow, plus one in Google+) but very lit ...

2016

Learning Explainable User Sentiment and Preferences for Information Filtering

Nikolaos Pappas

In the last decade, online social networks have enabled people to interact in many ways with each other and with content. The digital traces of such actions reveal people's preferences towards online content such as news or products. These traces often res ...

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

Social Interface and Interaction Design for Group Recommender Systems

Yu Chen

Group recommender systems suggest items of interest to a group of people. Traditionally, group recommenders provide recommendations by aggregation the group membersâ preferences. Nowadays, there is a trend of decentralized group recommendation process th ...

EPFL2015

MEM0R1ES: Memory-based Information Systems

Michele Catasta

The advent of the Web reshaped the way in which humans memorize information, arguably unlike any other technological advance of the last decades. Rather than remembering the information itself, people are primed to find the needed information through Web s ...

EPFL2015

Comparing the Predictive Capability of Social and Interest Affinity for Recommendations

Karl Aberer, Anne-Marie Kermarrec, Alexandra Olteanu

The advent of online social networks created new prediction opportunities for recommender systems: instead of relying on past rating history through the use of collaborative filtering (CF), they can leverage the social relations among users as a predictor ...

Springer-Verlag Berlin2014

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