We have proposed a cyberbullying detection system to address this issue. In this work, we proposed a deep learning framework that will evaluate real-time twitter tweets or social media posts as well as correctly identify any cyberbullying content in them.

Cyberbullying Detection implements our coded, machine learning algorithms, in finding a negative comment from the messages it receives by a user. The algorithm first gives the message a value and then based on our pre trained data, it decides if the comment is harsh enough to …

These results pave the way for more effective cyberbullying detection in emerging multimodal (audio, visual, virtual reality) social interaction spaces.

automated cyberbullying detection systems that can accurately identify harassing messages at scale. Recent advances in deep learning have shown promising results in text and image classification tasks, presenting an opportunity for developing robust cyberbullying detection models. This paper explores the application of deep learning

Oct 1, 2021 · Al-garadi et al. (2016) proposed a cyberbullying detection method by identifying characteristic features (e.g., user ID, username, user biography). In the study, various classifiers were applied to the collected data from Twitter.

Aug 20, 2024 · Cyberbullying Detection uses our programmed, machine-learning algorithms to detect harmful comments in communications received from a user. The algorithm assigns a value to the message and then determines whether or not the remark is severe enough to be changed based on using pre-trained data.

May 10, 2023 · This research developed an automatic system for cyberbullying detection with two approaches: Conventional Machine Learning and Transfer Learning. This research adopted AMiCA data encompassing significant amount of cyberbullying context and structured annotation process.

Deep learning-based models have made their way into the detection of cyberbullying occurrences, claiming to be able to overcome the limits of conventional models and significantly enhance detection performance.

In recent studies, deep learning based models have found their way in the detection of cyberbullying incidents, claiming that they can overcome the limitations of the conventional models, and improve the detection performance. In this paper, we investigate the findings of …

We examine the ethical and privacy issues surrounding XAI in this setting while presenting many case cases. Additionally, we compare XAI-driven models with conventional AI techniques and give an...