This paper presents and evaluates work on the development of an artificial intelligence (AI) anti-bullying system. The system is designed to identify coordinated bullying attacks via social media and other mechanisms, characterize them and propose remediation and response activities to them. In particular, a large language model (LLM) is used to populate an enhanced expert system-based network model of a bullying attack. This facilitates analysis and remediation activity - such as generating report messages to social media companies - determination. The system is described and the efficacy of the LLM for populating the model is analyzed herein.
@article{arxiv.2408.10417,
title = {Development of an AI Anti-Bullying System Using Large Language Model Key Topic Detection},
author = {Matthew Tassava and Cameron Kolodjski and Jordan Milbrath and Adorah Bishop and Nathan Flanders and Robbie Fetsch and Danielle Hanson and Jeremy Straub},
journal= {arXiv preprint arXiv:2408.10417},
year = {2024}
}