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Publications associées (9)

Page 1 sur 1

Learning Graph Influence From Social Interactions

Ali H. Sayed, Virginia Bordignon, Augusto José Rabelo Almeida Santos

In social learning, agents form their opinions or beliefs about certain hypotheses by exchanging local information. This work considers the recent paradigm of weak graphs, where the network is partitioned into sending and receiving components, with the for ...

IEEE2020

From Anomaly Detection to Rumour Detection using Data Streams of Social Platforms

Quoc Viet Hung Nguyen, Thành Tâm Nguyên

Social platforms became a major source of rumours. While rumours can have severe real-world implications, their detection is notoriously hard: Content on social platforms is short and lacks semantics; it spreads quickly through a dynamically evolving netwo ...

ASSOC COMPUTING MACHINERY2019

Graph-based Rumour Detection for Social Media

Thành Tâm Nguyên

Social platforms became a major source of rumours. While rumours can have severe real-world implications, their detection is notoriously hard: Content on social platforms is short and lacks semantics; it spreads quickly through a dynamically evolving netwo ...

2019

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

Potentials of Negative Emissions in the Design of Climate Agreements

Marc Vielle, Frédéric Louis François Babonneau

The aim of this paper is to explore the long-term relevance of negative emissions for the attainment of Paris agreement goals. For this purpose, we extend a game theoretic meta-model used to assess the future of Paris agreement to the time horizon 2100 and ...

2019

Fighting Rumours on Social Media

Chi Thang Duong

With the advance of social platforms, people are sharing contents in an unprecedented scale. This makes social platforms an ideal place for spreading rumors. As rumors may have negative impacts on the real world, many rumor detection techniques have been p ...

2018

Predicting the Success of Online Petitions Leveraging Multidimensional Time-Series

Karl Aberer, Philippe Cudré-Mauroux, Julia Proskurnia

Applying classical time-series analysis techniques to online content is challenging, as web data tends to have data quality issues and is often incomplete, noisy, or poorly aligned. In this paper, we tackle the problem of predicting the evolution of a time ...

International World Wide Web Conferences Steering Committee Republic and Canton of Geneva, Switzerland ©20172017

Please Sign to Save... : How Online Environmental Petitions Succeed

Karl Aberer, Philippe Cudré-Mauroux, Julia Proskurnia

Social media have become one of the key platforms to support the debate on climate change. In particular, Twitter allows easy information dissemination when running environmental campaigns. Yet, the dynamics of these campaigns on social platforms still rem ...

AAAI Press2016

Meta-analysis of incomplete microarray studies

Anthony Christopher Davison, Darlene Goldstein, Alix Corinne Josiane Colette Zollinger

Meta-analysis of microarray studies to produce an overall gene list is relatively straightforward when complete data are available. When some studies lack information, for example, having only a ranked list of genes instead of complete primary data, it is ...

Oxford University Press2015