Misinformation such as fake news and rumors is a serious threat for information ecosystems
and public trust. The emergence of large language models (LLMs) has great potential to …

Natural Language Generation (NLG) has improved exponentially in recent years thanks to
the development of sequence-to-sequence deep learning technologies such as Transformer …

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

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 …

Fake news is a real problem in today's world, and it has become more extensive and harder
to identify. A major challenge in fake news detection is to detect it in the early phase. Another …

As online content continues to grow, so does the spread of hate speech. We identify and
examine challenges faced by online automatic approaches for hate speech detection in text …

Recently, the use of social networks such as Facebook, Twitter, and Sina Weibo has
become an inseparable part of our daily lives. It is considered as a convenient platform for …

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 …

Detecting fake news requires both a delicate sense of diverse clues and a profound
understanding of the real-world background, which remains challenging for detectors based …

Fact-checking is the task of verifying the veracity of claims by assessing their assertions
against credible evidence. The vast majority of fact-checking studies focus exclusively on …