Fact-checking has become increasingly important due to the speed with which both
information and misinformation can spread in the modern media ecosystem. Therefore …

With the advent of social media, an increasing number of netizens are sharing and reading
posts and news online. However, the huge volumes of misinformation (eg, fake news and …

The recent serious cases of spreading false information have posed a significant threat to
the social stability and even national security, urgently requiring all circles to respond …

Rumors spread through the Internet, especially on Twitter, have harmed social stability and
residents' daily lives. Recently, in addition to utilizing the text features of posts for rumor …

A number of exciting advances have been made in automated fact-checking thanks to
increasingly larger datasets and more powerful systems, leading to improvements in the …

As social media becomes increasingly prominent in our day to day lives, it is increasingly
important to detect informative content and prevent the spread of disinformation and …

Fact verification systems typically rely on neural network classifiers for veracity prediction,
which lack explainability. This paper proposes ProoFVer, which uses a seq2seq model to …

Predicting the diffusion cascades is a critical task to understand information spread on social
networks. Previous methods usually focus on the order or structure of the infected users in a …

Researchers have exerted tremendous effort in designing ways to detect and identify rumors
automatically. Traditional approaches focus on feature engineering. They require lots of …

Information diffusion prediction is fundamental to understand the structure and organization
of the online social networks, and plays a crucial role to blocking rumor spread, influence …