The success of social media platforms has facilitated the emergence of various forms of online abuse within digital communities. This abuse manifests in multiple ways, including hate speech, cyberbullying, emotional abuse, grooming, and sexting. In this paper, we present a comprehensive analysis of the different forms of abuse prevalent in social media, with a particular focus on how emerging technologies, such as Language Models (LMs) and Large Language Models (LLMs), are reshaping both the detection and generation of abusive content within these networks. We delve into the mechanisms through which social media abuse is perpetuated, exploring the psychological and social impact. Additionally, we examine the dual role of advanced language models-highlighting their potential to enhance automated detection systems for abusive behavior while also acknowledging their capacity to generate harmful content. This paper aims to contribute to the ongoing discourse on online safety and ethics, offering insights into the evolving landscape of cyberabuse and the technological innovations that both mitigate and exacerbate it.

本文针对社交媒体中普遍存在的网络滥用问题进行全面分析，探讨了语言模型和大语言模型如何改变滥用内容的检测和生成。研究发现，先进的语言模型能够提高滥用行为的自动检测系统，但也可能生成有害内容，旨在为在线安全和伦理的重要讨论提供见解。

使用领先语言模型和大语言模型的文本网络滥用检测调查