Deborah Hall

Title: Innovations in Cyberbullying Detection by Deborah Hall

Introduction

Deborah Hall is an accomplished inventor based in Phoenix, AZ. She has made significant contributions to the field of cyberbullying detection through her innovative patent. Her work focuses on developing systems and methods that enhance the detection of cyberbullying in social media environments.

Latest Patents

Deborah Hall holds a patent for "Systems and methods for unsupervised cyberbullying detection via time-informed Gaussian mixture model." This computer-implemented framework includes two main components: a representation learning network that encodes social media sessions by utilizing multi-modal features such as text, network, and time, and a multi-task learning network that fits comment inter-arrival times while estimating bullying likelihood based on a Gaussian Mixture Model. The system optimizes the parameters of both components to address the limitations of decoupled training. It features an unsupervised cyberbullying detection model that outperforms existing unsupervised models and achieves competitive results compared to supervised models.

Career Highlights

Deborah Hall is affiliated with Arizona State University, where she continues to advance her research in cyberbullying detection. Her innovative approach has garnered attention in the academic community and beyond.

Collaborations

Some of her notable coworkers include Lu Cheng and Kai Shu, who have contributed to her research endeavors.

Conclusion

Deborah Hall's work in cyberbullying detection represents a significant advancement in the field, showcasing her dedication to creating effective solutions for social media challenges. Her innovative patent highlights the importance of technology in addressing contemporary issues.