Development of an AI Anti-Bullying System Using Large Language Model Key Topic Detection

TL;DR

This paper introduces an AI anti-bullying system leveraging large language models to detect, analyze, and respond to coordinated social media bullying attacks, enhancing intervention strategies.

Contribution

It develops an LLM-based approach to populate an expert system model for bullying detection and response, demonstrating its effectiveness in analyzing social media attacks.

Findings

LLM effectively populates the bullying attack model

System can generate intervention reports

Enhanced detection of coordinated bullying attacks

Abstract

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.