1 code implementation • 24 Mar 2024 • Benjamin Icard, François Maine, Morgane Casanova, Géraud Faye, Julien Chanson, Guillaume Gadek, Ghislain Atemezing, François Bancilhon, Paul Égré
We present a corpus of 100 documents, OBSINFOX, selected from 17 sources of French press considered unreliable by expert agencies, annotated using 11 labels by 8 annotators.
no code implementations • 6 Feb 2024 • Géraud Faye, Benjamin Icard, Morgane Casanova, Julien Chanson, François Maine, François Bancilhon, Guillaume Gadek, Guillaume Gravier, Paul Égré
This paper investigates the language of propaganda and its stylistic features.
no code implementations • ICAART 2022 2022 • Maxime Prieur, Guillaume Gadek, Bruno Grilheres
This paper explores the use of Graph Neural Network models producing node embeddings, in order to solve the not fully addressed problem of detecting similar items stored in a knowledge base.
no code implementations • 27 Oct 2021 • Paul Guélorget, Benjamin Icard, Guillaume Gadek, Souhir Gahbiche, Sylvain Gatepaille, Ghislain Atemezing, Paul Égré
In this paper, we combine two independent detection methods for identifying fake news: the algorithm VAGO uses semantic rules combined with NLP techniques to measure vagueness and subjectivity in texts, while the classifier FAKE-CLF relies on Convolutional Neural Network classification and supervised deep learning to classify texts as biased or legitimate.
no code implementations • COLING 2020 • Ga{\'e}tan Baert, Souhir Gahbiche, Guillaume Gadek, Alexandre Pauchet
We show that a language model (BAERT) pre-trained on a large corpus (LAD) in the same language (Arabizi) as that of the fine-tuning dataset (SALAD), outperforms a state-of-the-art multi-lingual pretrained model (multilingual BERT) on a sentiment analysis task.