Amid the proliferation of misinformation on social networks, automated rumor detection has
emerged as a pivotal and pressing research domain. Nonetheless, current methodologies …

The widespread propagation of misinformation on social media platforms poses a significant
concern, prompting substantial endeavors within the research community to develop robust …

Using deep neural networks to detect fake news has gradually become an extremely
important field of research. Recent studies, which adopt fine-tuning BERT to detect fake …

The amount of news being consumed online has substantially expanded in recent years.
Fake news has become increasingly common, especially in regional languages like …

The creation and propagation of disinformation on social media is a growing concern. The
widespread dissemination of disinformation can have destructive effects on people's …

False news articles pose a serious challenge in today's information landscape, impacting
public opinion and decision-making. Efforts to counter this issue have led to research in …

We present a novel approach to detecting fake news in Internet of Things (IoT) applications.
By investigating federated learning and trusted authority methods, we address the issue of …

Past research suggests pre-trained word embedding strategies to assess and determine
feelings conveyed in various text documents. However, using a single word embedding …

The spread of false information in the digital age has led to serious threats about the veracity
and dependability of information traded online. Fake news can exacerbate social and …

Nowadays, we can see how social media networks are developing. We must accept the fact
that the opinion of an expert is frequently just as valuable and crucial as that of a non-expert …