Several studies applying Machine Learning to deception detection have been published in
the last decade. A rich and complex set of settings, approaches, theories, and results is now …

Social media following its introduction has witnessed a lot of scholarly attention in recent
years due to its growing popularity. These various social media sites have become the …

In the last years, the popularity of smartphones and social networks has been contributing to
the spread of fake news. Through these electronic media, this type of news can deceive …

News verification is a process of determining whether a particular news report is truthful or
deceptive. Deliberately deceptive (fabricated) news creates false conclusions in the readers' …

This paper furthers the development of methods to distinguish truth from deception in textual
data. We use rhetorical structure theory (RST) as the analytic framework to identify …

The ease with which information can be shared on social media has opened it up to abuse
and manipulation. One example of a manipulation campaign that has garnered much …

The goal of this chapter is to introduce readers to automated deception detection research,
with a cursory look at the roots of the field in pre-social media data types. My intent is to draw …

Fake news has gained prominence since the 2016 US presidential election as well as the
Brexit referendum. Fake news has abused not only the press but also the democratic rules …

Due to the constantly evolving social media and different types of sources of information, we
are facing different fake news and different types of misinformation. Currently, we are …

The paper proposes to use Rhetorical Structure Theory (RST) analytic framework to identify
systematic differences between deceptive and truthful stories in terms of their coherence and …