There is an increased demand for detecting online hate speech, especially with the recent
changing policies of hate content and free-of-speech right of online social media platforms …

In the trend of the accelerated progression of communication network technology, the
emergence of virtual communities (VCs), virtual societies (VSs), metaverse, and other …

Speech emotion recognition (SER) is a challenging task in human–computer interaction
(HCI) systems. One of the key challenges in speech emotion recognition is to extract the …

We inquire into different perspectives and patterns of problematizing online hate speech
within the social sciences from a systems-theoretical perspective. Our results identify five …

Social media platforms empower us in several ways, from information dissemination to
consumption. While these platforms are useful in promoting citizen journalism, public …

This paper proposes a deep neural network (DNN) approach for detecting fake profiles in
social networks. The DNN model is trained on a large dataset of real and fake profiles and is …

The proliferation of social media platforms, including Facebook and Twitter, has significantly
enhanced global communication and information exchange. Concomitantly, it has …

Social media facilitates communication and information sharing, but it also allows the
spreading of hate speech. Identifying hate speech using textual data is widely studied. While …

Social networking has become one of the most significant aspects of everyday lives since it
allows us to communicate with many people. Social networking is used for many purposes …

Automated hate speech detection is important to protecting people's dignity, online
experiences, and physical safety in Society 5.0. Transformers are sophisticated pre-trained …