Transformer architectures are highly expressive because they use self-attention
mechanisms to encode long-range dependencies in the input sequences. In this paper, we …

Social media has been one of the main information consumption sources for the public,
allowing people to seek and spread information more quickly and easily. However, the rise …

The COVID-19 pandemic period is approaching the two-year mark of its lifetime. During the
pandemic, the people experienced various restrictions and different problems were raised …

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 …

Short text information has considerable commercial value and immeasurable social value.
Natural language processing and short text sentiment analysis technology can organize and …

Social media has effectively become the prime hub of communication and digital marketing.
As these platforms enable the free manifestation of thoughts and facts in text, images and …

The remarkable success of Transformer-based embeddings in natural language tasks has
sparked interest among researchers in applying them to classify rumours on social media …

Recently, the emergence of social media has opened the way for online harassment in the
form of hate speech and offensive language. An automated approach is needed to detect …

While fake news is morally reprehensible, irresponsible parties intentionally use it to achieve
their goals by disseminating it to vulnerable and targeted groups. Machine learning …

In the past decade, deep neural networks have been widely introduced into remote sensing
image interpretation tasks. Exploring how to improve the model at some critical points, such …