The increasing amount of fake news is a growing problem that will progressively worsen in
our interconnected world. Machine learning, particularly deep learning, is being used to …

Though a fair amount of research is being done to address disinformation in online social
media, it has so far managed to stay ahead of the researchers' learning curves forcing the …

Obtaining information about destinations and services they provide is ever more based on
user-generated content (UGC), which includes reviews of tourism services as well as …

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 …

Explainability in the field of event detection is a new emerging research area. For
practitioners and users alike, explainability is essential to ensuring that models are widely …

One of the serious consequences of social media usage is fake information dissemination
that locomotes society towards negativity. Existing solutions focus on supervised fake news …

VAGO est un outil en ligne de mesure du vague et de la subjectivité dans le discours, fondé
sur une base de données lexicale annotée ainsi que sur des règles expertes. VAGO est …

With growing hate and discrimination based on caste and race, Islamophobia is one of the
major and most populated phenomena nowadays. Islamophobia, in general refers to …

This book explores emotion detection within Natural Language Processing (NLP) by
focusing on categorical and dimensional models of emotion detection. It provides a …

News articles analysis may be oversimplified when restricted to detecting classes of interest
already benefiting from trustworthy labeled datasets, like political affiliation or fakeness …