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YouTube is a major social media platform that plays a significant role in digital culture, with content creators at its core. These creators often engage in controversial behaviour to drive engagement, which can foster toxicity. This paper presents a ...

The proliferation of hate speech on digital platforms has become a significant issue, and automated content moderation systems built on machine learning are a proposed solution. However, they face challenges in multilingual and low-resource settings due ...

This study evaluates the effectiveness of machine learning (ML) and deep learning (DL) models in detecting COVID-19-related misinformation on online social networks (OSNs), aiming to develop more effective tools for countering the spread of health ...

The non-consensual spread of intimate images and videos is a problematic phenomenon exacerbated by the rise of unmoderated instant messaging platforms like Telegram, where anonymity guarantees meet a loose regulatory framework. The popularity of ...

This paper presents a study on the application of Heterogeneous Graph Neural Networks (HGNNs) for enhancing the security of complex social systems by identifying illicit and malicious behaviors. We focus on digital asset tokenization, a key component in ...

Web3 describes the next generation of the Internet, built on top of various technologies, such as Blockchain Technology, Semantic Web, etc. Web3 proposal claims a vision of the Internet that can cut the intermediation of Big tech companies by completely ...