Online social networks (OSNs) are rapidly growing and have become a huge source of all
kinds of global and local news for millions of users. However, OSNs are a double-edged …

The emergence of various social networks has generated vast volumes of data. Efficient
methods for capturing, distinguishing, and filtering real and fake news are becoming …

The explosion of social media allowed individuals to spread information without cost, with
little investigation and fewer filters than before. This amplified the old problem of fake news …

The proliferation of false information is a growing problem in today's dynamic online
environment. This phenomenon requires automated detection of fake news to reduce its …

Over the recent years, the growth of online social media has greatly facilitated the way
people communicate with each other. Users of online social media share information …

Nowadays, fake news detection, which aims to verify whether a news document is trusted or
fake, has become urgent and important. Most existing methods rely heavily on linguistic and …

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 …

In recent years, to mitigate the problem of fake news, computational detection of fake news
has been studied, producing some promising early results. While important, however, we …

The explosive growth in fake news and its erosion to democracy, justice, and public trust has
increased the demand for fake news detection and intervention. This survey reviews and …

We propose Factual News Graph (FANG), a novel graphical social context representation
and learning framework for fake news detection. Unlike previous contextual models that …