Including Images into Message Veracity Assessment in Social Media

no code implementations • 20 Jul 2020 • Abderrazek Azri, Cécile Favre, Nouria Harbi, Jérôme Darmont

The extensive use of social media in the diffusion of information has also laid a fertile ground for the spread of rumors, which could significantly affect the credibility of social media.

MONITOR: A Multimodal Fusion Framework to Assess Message Veracity in Social Networks

no code implementations • 6 Sep 2021 • Abderrazek Azri, Cécile Favre, Nouria Harbi, Jérôme Darmont, Camille Noûs

Then, we introduce the Multimodal fusiON framework to assess message veracIty in social neTwORks (MONITOR), which exploits all message features (i. e., text, social context, and image features) by supervised machine learning.

BIG-bench Machine Learning Image Quality Assessment

Calling to CNN-LSTM for Rumor Detection: A Deep Multi-channel Model for Message Veracity Classification in Microblogs

no code implementations • 11 Oct 2021 • Abderrazek Azri, Cécile Favre, Nouria Harbi, Jérôme Darmont, Camille Noûs

Yet, to the best of our knowledge, exploiting images and sentiments is little investigated. Considering the available multimodal features from microblogs, notably, we propose in this paper an end-to-end model called deepMONITOR that is based on deep neural networks and allows quite accurate automated rumor verification, by utilizing all three characteristics: post textual and image contents, as well as sentiment.

Opinion Mining Sentiment Analysis +1

Rumor Classification through a Multimodal Fusion Framework and Ensemble Learning

no code implementations • 4 Jan 2023 • Abderrazek Azri, Cécile Favre, Nouria Harbi, Jérôme Darmont, Camille Noûs

The proliferation of rumors on social media has become a major concern due to its ability to create a devastating impact.

Ensemble Learning Image Quality Assessment