A protuberant issue of the present time is that, organizations from different domains are
struggling to obtain effective solutions for detecting online-based fake news. It is quite …

Automatic elicitation of semantic information from natural language texts is an important
research problem with many practical application areas. Especially after the recent …

Cross-modal learning is essential to enable accurate fake news detection due to the fast-
growing multimodal contents in online social communities. A fundamental challenge of …

Society and individuals are negatively influenced both politically and socially by the
widespread increase of fake news either way generated by humans or machines. In the era …

Stance detection is an evolving opinion mining research area motivated by the vast increase
in the variety and volume of user-generated content. In this regard, considerable research …

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 …

Fake news is risky, since it has been created to manipulate readers' opinions and beliefs. In
this work, we compared the language of false news to the real one of real news from an …

To provide accurate and explainable misinformation detection, it is often useful to take an
auxiliary source (eg, social context and knowledge base) into consideration. Existing …

The development of social media has revolutionized the way people communicate, share
information and make decisions, but it also provides an ideal platform for publishing and …

Fake news detection (FND) has attracted much research interests in social forensics. Many
existing approaches introduce tailored attention mechanisms to fuse unimodal features …