Recently, the use of social networks such as Facebook, Twitter, and Sina Weibo has
become an inseparable part of our daily lives. It is considered as a convenient platform for …

The global spread of the novel coronavirus is affected by the spread of related
misinformation—the so-called COVID-19 Infodemic—that makes populations more …

Social media are digitalizing massive amounts of users' cognitions in terms of timelines and
emotional content. Such Big Data opens unprecedented opportunities for investigating …

Modeling discussions on social networks is a challenging task, especially if we consider
sensitive topics, such as politics or healthcare. However, the knowledge hidden in these …

With a substantial proportion of the population currently hesitant to take the COVID-19
vaccine, it is important that people have access to accurate information. However, there is a …

Despite the increasing limitations for unvaccinated people, in many European countries
there is still a non-negligible fraction of individuals who refuse to get vaccinated against …

Context The F-measure has been widely used as a performance metric when selecting
binary classifiers for prediction, but it has also been widely criticized, especially given the …

In this paper we investigate what folk models of misinformation exist through semi-structured
interviews with a sample of 235 social media users. Work on social media misinformation …

Abstract Multimodal Named Entity Recognition (MNER) is a fundamental task in the field of
natural language processing for social media posts. Current MNER models fail to deal with …

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 …