Publication

A large scale study of reader interactions with images on Wikipedia

Publications associées (33)

Content Moderation in Online Platforms

Manoel Horta Ribeiro

A critical role of online platforms like Facebook, Wikipedia, YouTube, Amazon, Doordash, and Tinder is to moderate content. Interventions like banning users or deleting comments are carried out thousands of times daily and can potentially improve our onlin ...
EPFL2024

Volunteer contributions to Wikipedia increased during COVID-19 mobility restrictions

Robert West, Manoel Horta Ribeiro

Wikipedia, the largest encyclopedia ever created, is a global initiative driven by volunteer contributions. When the COVID-19 pandemic broke out and mobility restrictions ensued across the globe, it was unclear whether contributions to Wikipedia would decr ...
NATURE PORTFOLIO2021

Dynamic pattern recognition in large-scale graphs with applications to social networks

Volodymyr Miz

A graph is a versatile data structure facilitating representation of interactions among objects in various complex systems. Very often these objects have attributes whose measurements change over time, reflecting the dynamics of the system. This general da ...
EPFL2020

A Graph-structured Dataset for Wikipedia Research

Pierre Vandergheynst, Nicolas Aspert, Volodymyr Miz, Benjamin Ricaud

Wikipedia is a rich and invaluable source of information. Its central place on the Web makes it a particularly interesting object of study for scientists. Researchers from different domains used various complex datasets related to Wikipedia to study langua ...
ACM2019

Why the World Reads Wikipedia: Beyond English Speakers

Robert West

As one of the Web's primary multilingual knowledge sources, Wikipedia is read by millions of people across the globe every day. Despite this global readership, little is known about why users read Wikipedia's various language editions. To bridge this gap, ...
ASSOC COMPUTING MACHINERY2019

Controlling motion artefact levels in MR images by suspending data acquisition during periods of head motion

Bogdan Draganski

Purpose: Head movements are a major source of MRI artefacts. Prospective motion correction techniques significantly improve data quality, but strong motion artefacts may remain in the data. We introduce a framework to suspend data acquisition during period ...
2018

Wikipedia's Miracle

Frédéric Kaplan, Nicolas Nova

Wikipedia has become the principle gateway to knowledge on the web. The doubts about information quality and the rigor of its collective negotiation process during its first couple of years have proved unfounded. Whether this delights or horrifies us, Wiki ...
EPFL PRESS2016

WebAL Comes of Age: A Review of the First 21 Years of Artificial Life on the Web

Joshua Evan Auerbach, Sebastian Risi, Jason Yosinski

We present a survey of the first 21 years of web-based artificial life (WebAL) research and applications, broadly construed to include the many different ways in which artificial life and web technologies might intersect. Our survey covers the period from ...
Mit Press2016

Wikipedia Chemical Structure Explorer: substructure and similarity searching of molecules from Wikipedia

Luc Patiny, Michaël Giuseppe Zasso

Background: Wikipedia, the world's largest and most popular encyclopedia is an indispensable source of chemistry information. It contains among others also entries for over 15,000 chemicals including metabolites, drugs, agrochemicals and industrial chemica ...
Biomed Central Ltd2015

Semantic-Improved Color Imaging Applications: It Is All About Context

Sabine Süsstrunk, Albrecht Johannes Lindner

Abstract—Multimedia data with associated semantics is omnipresent in today’s social online platforms in the form of keywords, user comments and so forth. This article presents a statistical framework designed to infer knowledge in the imaging domain from t ...
2015

Graph Chatbot

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.