Online social networks (OSNs) are part of daily life of human beings. Millions of users are
connected through online social networks. Due to very large number of users and huge …

Recently, neural networks based on multi-task learning have achieved promising
performance on fake news detection, which focus on learning shared features among tasks …

Enormous hope in the efficacy of vaccines became recently a successful reality in the fight
against the COVID-19 pandemic. However, vaccine hesitancy, fueled by exposure to social …

The majority of existing methods for fake news detection universally focus on learning and
fusing various features for detection. However, the learning of various features is …

The construction industry suffers from workplace accidents, including injuries and fatalities,
which represent a significant economic and social burden for employers, workers, and …

The rise of social media platforms has led to an increase in the flow and dissemination of
information, but it has also made generating and spreading rumors easier. Rumor detection …

Deep reinforcement learning (DRL), which combines deep learning with reinforcement
learning, has achieved great success recently. In some cases, however, during the learning …

Although deep learning has reached a higher accuracy for video content analysis, it is not
satisfied with practical application demands of porn streamer recognition in live video …

Existing methods utilized single words as text features. Some words contain multiple
meanings, and it is difficult to distinguish its specific classification according to a single word …

Covid-19 out broke gave an extreme impact to the globe, imposing a challenge to health
publicly and causing social interruptions. As a result, the role of mainstream media in …